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free_courses.json

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+[
+    {
+        "title": "Frameworks for Effective Problem Solving",
+        "lessons": "18 Lessons",
+        "description": "Master the art of structured thinking to tackle complex challenges effectively. This course covers essential frameworks like SMART, MECE, and Issue Trees, guiding you in defining and solving problem statements while avoiding common pitfalls. Learn practical, step-by-step methods to enhance decision-making and problem-solving skills."
+    },
+    {
+        "title": "Anyone can Build AI Agents - Free Course",
+        "lessons": "5 Lessons",
+        "description": " This beginner-friendly course is designed for individuals who want to harness Generative AI potential without diving into code. In this course, you learn to create, deploy, and customize an AI agent using an intuitive no-code platform Wordware. Step by step, we guide you through setting up your agent to handle real-world tasks. Throughout the course, you explore various tools, leverage pre-built AI models, and customize your agent behavior without writing a single line of code. By the end, you will be able to build your own AI agent ready to tackle business and personal projects, with the skills to innovate faster and more efficiently."
+    },
+    {
+        "title": "A Comprehensive Learning Path to Become a Data Analyst in 2025",
+        "lessons": "298 Lessons",
+        "description": "we are here to help you take your first steps into the world of data analytics! Here’s the learning path for people who want to become a data analyst in 2025. We have arranged and compiled all the best resources in a structured manner so that you have a unified resource to become a successful data analyst. Moreover, we have added the most in-demand skills for the year 2025 for data analyst along with exercises and assignments."
+    },
+    {
+        "title": "Reimagining GenAI: Common Mistakes and Best Practices for Success",
+        "lessons": "6 Lessons",
+        "description": "Generative AI is transforming industries, but implementation challenges often hinder its success. This course, led by experienced GenAI expert Shabazz Mohammed, dives deep into the pitfalls of adopting generative AI and provides actionable best practices to overcome them.Learn from real-world scenarios, understand why hi-fi demos fail in production, and gain insights into scalable, ethical, and ROI-driven AI adoption."
+    },
+    {
+        "title": "Coding a ChatGPT-style Language Model from Scratch in PyTorch",
+        "lessons": "7 Lessons",
+        "description": "Master the art of building a ChatGPT-style language model from scratch with PyTorch. In this course, you'll explore essential NLP concepts, implement transformers, and create a decoder-only architecture step-by-step. Guided by expert tutorials, gain practical skills to develop advanced AI models tailored for real-world applications."
+    },
+    {
+        "title": "Mastering Multilingual GenAI Open-Weights for Indic Languages",
+        "lessons": "9 Lessons",
+        "description":"Mastering Multilingual GenAI – Open-Weights for Indic Languages is a course designed to equip you with the knowledge to develop state-of-the-art multilingual AI models using open-weight architectures. Focusing on low-resource languages, particularly Indic languages, the course covers essential topics like multilingual AI training, instruction fine-tuning, model building, and performance evaluation."
+    },
+    {
+        "title": "Learning Autonomous Driving Behaviors with LLMs & RL",
+        "lessons": "6 Lessons",
+        "description":" This beginner-friendly course is designed for individuals who want to harness Generative AI potential without diving into code. In this course, you learn to create, deploy, and customize an AI agent using an intuitive no-code platform Wordware. Step by step, we guide you through setting up your agent to handle real-world tasks. Throughout the course, you explore various tools, leverage pre-built AI models, and customize your agent behavior without writing a single line of code. By the end, you will be able to build your own AI agent ready to tackle business and personal projects, with the skills to innovate faster and more efficiently."
+        
+    },
+    {
+        "title": "GenAI Applied to Quantitative Finance: For Control Implementation",
+        "lessons": "5 Lessons",
+        "description":"This course explores the application of Generative AI in quantitative finance, focusing on building sustainable trading algorithms through keyword extraction, sentiment analysis, and time-series forecasting. Learn to predict commodity prices, such as gold, by integrating data from financial news sources, leveraging sentiment analysis, and optimizing models for robust trading signals."    },
+    {
+        "title": "Navigating LLM Tradeoffs: Techniques for Speed, Cost, Scale & Accuracy",
+        "lessons": "6 Lessons",
+        "description": "This course provides a concise guide to optimizing Large Language Models (LLMs) by navigating tradeoffs in speed, cost, scale, and accuracy. Learn practical techniques like LoRA, model quantization, and parameter-efficient fine-tuning to improve performance while reducing costs. You'll explore various deployment strategies and understand how to evaluate LLMs using industry-standard benchmarks, making this course ideal for anyone seeking efficient, scalable AI solutions"},
+    {
+        "title": "Creating Problem-Solving Agents using GenAI for Action Composition",
+        "lessons": "6 Lessons",
+        "description":  "This introductory course provides a concise overview of Agentic AI systems, covering their evolution, current state, and practical applications. You will explore key topics including the history of Agentic AI systems, the role of agents today, multi-agent systems, and practical solutions for implementing them. Perfect for those seeking a foundational understanding of intelligent Agentic AI systems in action."  },
+    {
+        "title": "Improving Real, World RAG Systems: Key Challenges & Practical Solutions",
+        "lessons": "12 Lessons",
+        "description": "This course explores the key challenges in building real-world Retrieval-Augmented Generation (RAG) systems and provides practical solutions. Topics include improving data retrieval, dealing with hallucinations, context selection, and optimizing system performance using advanced prompting, retrieval strategies, and evaluation techniques. Through hands-on demos, you will gain insights into better chunking, embedding models, and agentic RAG systems for more robust, real-world applications." },
+    {
+        "title": "Framework to Choose the Right LLM for your Business",
+        "lessons": "6 Lessons",
+        "description": "This course will guide you through the process of selecting the most suitable Large Language Model (LLM) for various business needs. By examining factors such as accuracy, cost, scalability, and integration, you will understand how different LLMs perform in specific scenarios, from customer support to healthcare and strategy development. The course emphasizes practical decision-making with real-world case studies, helping businesses navigate the rapidly evolving LLM landscape effectively."
+
+    },
+    {
+        "title": "Building Smarter LLMs with Mamba and State Space Model",
+        "lessons": "14 Lessons",
+        "description":   "Unlock the Power of State Space Models (SSM) like Mamba with our comprehensive course designed for AI professionals, data scientists, and NLP enthusiasts. Master the art of integrating SSM with deep learning, unravel the complexities of models like Mamba, and elevate your understanding of Generative AI's newest and most innovative models. This course is designed to equip you with the skills needed to understand these cutting-edge AI models and how they work, making you proficient in the latest AI techniques and architectures." },
+    {
+        "title": "Generative AI - A Way of Life - Free Course",
+        "lessons": "31 Lessons",
+        "description": "This course is a transformative journey tailored for beginners and delves into AI-powered text and image generation using leading tools like ChatGPT, Microsoft Copilot, and DALL·E3. Learn practical applications across industries, ethical considerations, and best practices. Whether you're a content creator, business innovator, or AI enthusiast, gain the expertise to harness Generative AI's full potential and drive innovation in your field."   },
+    {
+        "title": "Building LLM Applications using Prompt Engineering - Free Course",
+        "lessons": "18 Lessons",
+        "description":  "This course will provide you with a hands-on understanding of building LLM applications and mastering prompt engineering techniques. By the end of the course, you will be proficient in implementing and fine-tuning these techniques to enhance generative AI model performance. You'll learn to apply various prompting methods and build chatbots on enterprise data, equipping you with the skills to improve conversational AI systems in real-world projects."  },
+    {
+        "title": "Building Your First Computer Vision Model - Free Course",
+        "lessons": "7 Lessons",
+        "description": "This course will help you gain a deep understanding of Computer Vision and build advanced CV models using the PyTorch framework. With a carefully curated list of resources and exercises, this course is your guide to becoming a Computer Vision expert. Master the techniques to build convolutional neural networks, and classify images."   },
+    {
+        "title": "Bagging and Boosting ML Algorithms - Free Course",
+        "lessons": "16 Lessons",
+        "description": "This course will provide you with a hands-on understanding of Bagging and Boosting techniques in machine learning. By the end of the course, you will be proficient in implementing and tuning these ensemble methods to enhance model performance. You'll learn to apply algorithms like Random Forest, AdaBoost, and Gradient Boosting to a real-world dataset, equipping you with the skills to improve predictive accuracy and robustness in your projects."   },
+    {
+        "title": "MidJourney: From Inspiration to Implementation - Free Course",
+        "lessons": "5 Lessons",
+        "description": "This course will provide you with a practical understanding of MidJourney tools. By the end of the course, you will be able to utilize MidJourney effectively and explore alternative tools for your creative projects. You'll learn how to draw inspiration, use MidJourney's features, and understand its applications through engaging lessons." },
+    {
+        "title": "Understanding Linear Regression - Free Course",
+        "lessons": "10 Lessons",
+        "description": "This free course will help you understand the fundamentals of linear regression in a straightforward manner. By the end of this course, you will be able to build predictive models using linear regression techniques. With a carefully curated list of resources and exercises, this course serves as your comprehensive guide to mastering linear regression. " },
+    {
+        "title": "The Working of Neural Networks - Free Course",
+        "lessons": "11 Lessons",
+        "description":   "This free course will help you understand the end-to-end working of neural networks in a simple manner. By the end of this course, you will be able to build advanced Deep Learning models using the PyTorch framework. With a carefully curated list of resources and exercises, this course serves as your comprehensive guide to mastering deep learning. It is recommended that you complete the advanced Machine Learning course before taking up this course." },
+    {
+        "title": "The A to Z of Unsupervised ML - Free Course",
+        "lessons": "13 Lessons",
+        "description":  "Unsupervised machine learning helps uncover hidden patterns and structures in data without labeled examples. It is essential for exploratory data analysis, reducing dimensionality, and discovering intrinsic relationships within datasets. Mastering unsupervised techniques enhances data preprocessing and drives insights in complex datasets where labels are scarce or unavailable." },
+    {
+        "title": "Building Your first RAG System using LlamaIndex - Free Course",
+        "lessons": "12 Lessons",
+        "description":  "This course will guide you through building your first Retrieval-Augmented Generation (RAG) system using LlamaIndex. You will start with data ingestion by loading a file into the system, followed by indexing the data for efficient retrieval. Next, you will set up retrieval configurations and use a response synthesizer to combine data into a coherent response. Finally, you will employ a query engine to generate responses. By the end of this course, you will have a solid understanding of these processes and be able to build an RAG system using LlamaIndex code effectively."  },
+    {
+        "title": "Data Preprocessing on a Real-World Problem Statement - Free Course",
+        "lessons": "13 Lessons",
+        "description":  "This course will help you get a practical understanding of Data Preprocessing. After this course, you can work on any data and prepare it for modelling. With a carefully curated list of resources, this course is your first step to becoming a Data Scientist. By the end of the course, you will have mastered techniques like EDA and Missing Value Treatment."  },
+    {
+        "title": "Exploring Stability.AI - Free Course",
+        "lessons": "7 Lessons",
+        "description":  "This course will give you a practical understanding of Stability.AI tools. By the end of the course, you will be able to deploy and customize SD WebUI, and use the Automatic1111 WebUI on RunPod GPU environments. You'll learn to install, set up, generate, and fine-tune SD WebUI settings, equipping you with the skills to harness Stability.AI's full potential for your projects."  },
+    {
+        "title": "Building a Text Classification Model with Natural Language Processing - Free Course",
+        "lessons": "16 Lessons",
+        "description":"Gain practical insights into Natural Language Processing (NLP) with our comprehensive course. Learn to build NLP models using PyTorch, delve into classification models, and apply techniques like bag-of-words, count vectorizer and so on. Perfect for professionals seeking to enhance their skills and aspiring students entering the tech industry." },
+    {
+        "title": "Getting Started with Large Language Models",
+        "lessons": "18 Lessons",
+        "description": "This course will help you gain a comprehensive understanding of Large Language Models (LLMs) and develop advanced natural language processing (NLP) applications using the PyTorch framework. With a carefully curated list of resources and exercises, this course is your guide to becoming an expert in LLMs. Master the techniques to build and fine-tune LLMs, and generate human-like text."},
+    {
+        "title": "Introduction to Generative  AI",
+        "lessons": "9 Lessons",
+        "description": "This course will provide you with a comprehensive understanding of generative AI, including text and image generation techniques. By the end of the course, you will be have an understanding of using generative AI tools to create diverse content. You'll learn how generative AI works, engage in practical exercises, and gain the skills to implement these techniques in real-world projects." },
+    {
+        "title": "Exploring Natural Language Processing (NLP) using Deep Learning",
+        "lessons": "79 Lessons",
+        "description": "Natural Language Processing (NLP) is the hottest field in the data science space right now. The demand for NLP experts and data scientists is through the roof. We have seen a remarkable rise in the amount of research and breakthroughs in NLP recently. We can trace this recent rise to one (seismic) paper 'Attention is All You Need' by Google AI. This breakthrough has spawned so many new and exciting NLP libraries that enable us to work with text in ways that were previously limited to our imagination (or Hollywood). These NLP deep learning developments have spawned some mind-boggling applications. We are sure youve already interacted with and used some of them yourself Human-level chatbots (dialogue systems like Google Duplex and Meena) Text generation (Machines writing text from scrtach, such as OpenAI;s GPT-2 model). Here’s a quick list of the latest Natural Language Processing concepts in deep learning every NLP expert and even enthusiast should know:Language Modeling ,Sequence-to-Sequence Modeling, Attention Mechanism,Transformer Architecture ,Transfer Learning in NLP and much more! These are key NLP deep learning concepts you should master if you want to successfully navigate through the NLP goldmine." },
+    {
+        "title": "Getting Started with Deep Learning",
+        "lessons": "299 Lessons",
+        "description": "Deep learning algorithms are revolutionizing data science industry and disrupting several domains. From computer vision applications to natural language processing (NLP) use cases - every field is benefitting from use of Deep Learning models. This course starts by assuming no knowledge about Neural Networks and Deep Learning and introduces these subjects to the student one by one. The course helps you build a deep as well as intuitive understanding of what is Deep Learning, where can Deep Learning Models be applied and then helps you solve several real life problems using Keras and PyTorch frameworks" },
+    {
+        "title": "Nano Course: Dreambooth-Stable Diffusion for Custom Images",
+        "lessons": "13 Lessons",
+        "description":"Have you ever wondered how to turn your dreams into reality by creating images of your dog traveling around the world or yourself alongside Elon Musk or playing cricket with MSD? This is exactly where the dreambooth model comes into the picture. With the help of Dreambooth, you can personalize the stable diffusion for a particular subject. Given just 5 images of our subject, dreambooth can create new images across diverse scenes, poses, views, and lighting conditions that do not appear in the reference images. In this free nano course on Dreambooth, Sandeep will discuss the historical journey of stable diffusion, its current landscape, and a brief understanding of the stable diffusion training process. Then we will move on to the dreambooth, its training process and finetune dreambooth on our custom dataset."},
+    {
+        "title": "A Comprehensive Learning Path for Deep Learning in 2023",
+        "lessons": "72 Lessons",
+        "description": "The most common question we get from beginners in the field of Deep Learning is - Where to begin? The journey to becoming a Deep Learning expert can be difficult if one does not have the right resources to follow. There are a million resources to refer and it is tough to decide where to start from.We are here to help you take your first steps into the world of Deep Learning. Here is a free learning path for people who want to become a Deep Learning expert in 2023. We have arranged the best resources in a logical manner along with exercises to make sure that you only need to follow one single source to become a data scientist." },
+    {
+        "title": "A Comprehensive Learning Path to Become a Data Scientist in 2024",
+        "lessons": "389 Lessons",
+        "description": "The most common question we get from beginners in the field of Deep Learning is - Where to begin? The journey to becoming a Deep Learning expert can be difficult if one does not have the right resources to follow. There are a million resources to refer and it is tough to decide where to start from. We are here to help you take your first steps into the world of Deep Learning. Here is a free learning path for people who want to become a Deep Learning expert in 2023. We have arranged the best resources in a logical manner along with exercises to make sure that you only need to follow one single source to become a data scientist." },
+    {
+        "title": "Nano Course: Building Large Language Models for Code",
+        "lessons": "10 Lessons",
+        "description":"Where do I begin? Data science is such a huge field - where do you even start learning about Data Science?These are career-defining questions often asked by data science aspirants. There are a million resources out there to refer but the learning journey can be quite exhausting if you don’t know where to start. Don’t worry, we are here to help you take your first steps into the world of data science! Here’s the learning path for people who want to become a data scientist in 2023. We have arranged and compiled all the best resources in a structured manner so that you have a unified resource to become a successful data scientist. Moreover, we have added the most in-demand skills for the year 2023 for data scientists including storytelling, model deployment, and much more along with exercises and assignments."},
+    {
+        "title": "Nano Course: Cutting Edge LLM Tricks",
+        "lessons": "12 Lessons",
+        "description": "In this Free Nano GenAI Course on Building Large Language Models for Code, you will-Learn how to train LLMs for Code from Scratch covering Training Data Curation, Data Preparation, Model Architecture, Training, and Evaluation Frameworks. ,Explore each step in-depth, delving into the algorithms and techniques used to create StarCoder, a 15B code generation model trained on 80+ programming languages, Understand and learn the best practices to train your own StarCoder on the data"},
+    {
+        "title": "Certified AI & ML BlackBelt+ Program",
+        "lessons": "Lesson count not found",
+        "description": "There are multiple elements that go into becoming an AI expert. Data Science, Machine Learning and Deep Learning are the core components you would need in our journey to break into the wonderful world of AI applications. AI & ML BlackBelt+ is a thoughtfully curated program designed for anyone wanting to learn data science, machine learning, deep learning in their quest to become an AI professional. It all starts here, so are you ready to take the ride? You will get access to ALL the courses Analytics Vidhya has curated and designed as part of AI & ML Blackbelt+. What are you waiting for? Start your AI journey today!" },
+    {
+        "title": "Machine Learning Summer Training",
+        "lessons": "263 Lessons",
+        "description":  "If you are a college student and looking for summer training, then you are at the right place where Analytics Vidhya is providing its virtual training along with the mega hackathon for students all over the world to compete, win grand rewards and internship opportunities. Machine Learning Summer Training is an online program to build and enhance your programming and machine learning skills, led by the best industry experts and data science professionals. After completing this training you will be provided with a blockchain enabled certificate by Analytics Vidhya with lifetime validity. This is the perfect starting point to ignite your fledging machine learning career and take a HUGE step towards your dream data scientist role."  },
+    {
+        "title": "AI Ethics by Fractal",
+        "lessons": "5 Lessons",
+        "description": "AI has a huge influence on our lives. From typing on our smartphones, to personalized recommendations on our favourite shopping websites, intelligent machines are everywhere. Our interactions with technology have become more personalized, but with humans ultimately behind these creations, the question is: where does the responsibility lie? Why and how should we begin the AI ethics conversation at Fractal?" },
+    {
+        "title": "A Comprehensive Learning Path to Become a Data Engineer in 2022",
+        "lessons": "204 Lessons",
+        "description": "Where do I begin? Data Engineering is such a huge field - where do you even start learning about Data Engineering?These are career-defining questions often asked by data engineering aspirants. There are a million resources out there to refer but the learning journey can be quite exhausting if you don’t know where to start. Don’t worry, we are here to help you take your first steps into the world of data engineering! Here’s the learning path for people who want to become a data engineer in 2022. We have arranged and compiled all the best resources in a structured manner so that you have a unified resource to become a successful data engineer. Moreover, we have added the most in-demand skills for the year 2022 for data engineers including storytelling, model deployment, and much more along with exercises and assignments. " },
+
+    {
+        "title": "Certified Business Analytics Program",
+        "lessons": "11 courses",
+        "description":"With increase in data generated across the globe, the demand for Business Analytics professionals is rising continuously. In short, aiming for a role in Business Analytics has never been a better career choice! Certified Business Analytics Program aims to provide you all the tools and techniques, along with hands on experience you need to succeed as a Business Analytics professional. This program covers tools like Excel, Tableau, SQL, Python and covers all the techniques like Statistics and Exploratory Data Analysis. The program also covers Predictive modeling and basics of Machine Learning. More importantly, the program helps you prepare your Resume, prepares you for Business Analytics Interviews and provides one on one mentorship during the program."},
+        {
+        "title": "Certified Machine Learning Master's Program (MLMP)",
+        "lessons": "6 courses",
+        "description": "Structured thinking mindset to tackle data science challenges Learn the most popular language to work with Structured and Unstructured Data The most common language in the machine learning world to extract data – SQL Learn the art of exploratory data analysis to extract valuable insights Use simple and advanced time series forecasting models for deep learning Explore recommender systems and its applications in the industry Master machine learning algorithms end-to-end Deploy Machine Learning models into production Work on plenty of machine learning projects to enhance your industry value Methods to explain Machine Learning model to your customer" },
+    {
+        "title": "Certified Natural Language Processing Master’s Program",
+        "lessons": "7 courses",
+        "description": "Natural Language Processing (NLP) is one of the fastest growing field within Artificial Intelligence. It enables machines to understand information contained in any text. NLP bridges the gap between the abstract but omnipresent human languages with concise and concrete programming languages. As more and more organizations invest in data - they would need NLP experts. This comprehensive program empowers you to become an NLP practitioner, even if you are a beginner and have no prior knowledge of the concepts."},
+    {
+        "title": "Certified Computer Vision Master's Program",
+        "lessons": "6 courses",
+        "description": "We have designed this certified program for Computer Vision enthusiasts like you who are looking for a place to start. Computer Vision is currently among the hottest fields in the industry. The demand for computer vision experts is outstripping the supply! So you’ve picked the perfect time to get into this field. This comprehensive program powers you to become a computer vision expert. The beauty of this program is that it assumes no prior knowledge of concepts. We start from the ground up by learning the basics of Python, statistics, core machine learning algorithms & fundamentals of Deep Learning. Once your base is rock solid, jump over to the Computer Vision using Deep Learning course. It is designed to give you a taste of how the underlying techniques work in current State-of-the-Art Computer Vision systems, and walks you through remarkable Computer Vision applications in a hands-on manner so that you can create such solutions on your own. Object detection Face detection Image Classification Image Segmentation Image generation, and many others!" },
+    {
+        "title": "Applied Machine Learning - Beginner to Professional",
+        "lessons": "612 Lessons",
+        "description": "Machine Learning is re-shaping and revolutionising the world and disrupting industries and job functions globally. It is no longer a buzzword - many different industries have already seen automation of business processes and disruptions from Machine Learning. In this age of machine learning, every aspiring data scientist is expected to upskill themselves in machine learning techniques & tools and apply them in real-world business problems." },
+    {
+        "title": "Ace Data Science Interviews",
+        "lessons": "59 Lessons",
+        "description": "Are you trying to get into data science roles but getting rejected by employers? Are you scared of getting into data science interviews? Or don't know what to expect in data science interviews? This is just the course you need. While you might know the tools and techniques in data science, clearing a data science interview might still prove very difficult. You need to show your problem solving skills and technical prowess in these data science interviews. This course has been created based on hundreds of interviews we have taken, companies we have helped in data science interviews and several data science experts in the industry. Key learnings and takeaways from 'Ace Data Science Interviews' course: Understand different roles existing in data science ecosystem(e.g.Data Scientist, Data Engineers, Data Analyst etc.) Learn what skill sets required for each of these roles Understand different types of Interviews which happen in Data Science Industry Tips and tricks to Ace your Data Science Interviews How to build your digital presence including LinkedIn and GitHub profile Learn the process to create a professional experience for data science roles. Framework to solve Guesstimates and case studies used in data science interviews"},
+    {
+        "title": "Writing Powerful Data Science Articles",
+        "lessons": "6 Lessons",
+        "description": "This free crash course on writing powerful data science articles is conducted over two sessions of 1-hour each. Here’s the agenda for both sessions: Session 1: How to Write Powerful Data Science Articles This is where it all begins! The power of writing What should you write about? How to pick a topic your audience will like? The big question - HOW should you write an article that resonates with your audience? A quick demo of our writing platform (editor.analyticsvidhya.com) Session 2: Best Practices - Writing Articles that Grab your Reader’s Attention This is where we bring it all together. Tips on how to improve your article’s engagement Best practices for enhancing your article’s readability How to increase your article’s reach Examples, SEO best practices, tips and tricks to increase your article viewership"},
+    {
+        "title": "Machine Learning Certification Course for Beginners",
+        "lessons": "261 Lessons",
+        "description": "Python libraries like Numpy, Pandas, etc. to analyze your data efficiently. Importance of Statistics and Exploratory Data Analysis (EDA) in the data science field. Linear Regression, Logistic Regression, and Decision Trees for building machine learning models. Understand how to solve Classification and Regression problems using machine learning How to evaluate your machine learning models using the right evaluation metrics? Improve and enhance your machine learning model’s accuracy through feature engineering" },
+    {
+        "title": "Data Science Career Conclave",
+        "lessons": "6 Lessons",
+        "description": "In this exclusive course called the “Data Science Career Conclave”, Analytics Vidhya has brought together leading data science experts to share their view on a broad range of data science career topics. What is being covered in this Data Science Career Conclave? As we said, a broad range of topics related to transitioning into a data science career. Here’s a brief list of topics you can look forward to: Different Roles in Data Science - Which Role is Right for You? - by Mathangi Sri What are Hiring Managers Really Looking For? - by Kiran R How to Build your Digital Profile for Data Science - by Dipanjan Sarkar Panel Discussion: How can you Transition into Data Science in 12 Months?"},
+    {
+        "title": "Top Data Science Projects for Analysts and Data Scientists",
+        "lessons": "36 Lessons",
+        "description": "This is a very common question interviewers ask in data science interviews. We have conducted hundreds of these interviews for both data analyst and data scientist roles and this is quite often the jackpot question. This is especially true if you’re a fresher or a relative newcomer to data science. Just doing courses or attaining certifications isn’t good enough. Almost everyone we know holds certifications in various aspects of data science. It adds no value to your resume if you don’t combine it with practical experience. And that’s where open-source data science projects play such a key role!" },
+    {
+        "title": "Getting Started with Git and GitHub for Data Science Professionals",
+        "lessons": "20 Lessons",
+        "description": "The beauty of version control will be akin to a revelation. The way you can create a remote project and have all your team members work on different features parallelly yet independently but still have a stable running code at the end of the day - priceless! A lot of the problem we face in data science while working remotely and independently will be erased with a quick understanding of Git and GitHub."},
+    {
+        "title": "Machine Learning Starter Program",
+        "lessons": "3 courses",
+        "description": "A data scientist’s job is one of the most sought-after in the 21st century. Companies are increasingly looking for professionals with a variety of skills in Machine Learning. And that's what we are here to give you via our Machine Learning Starter Program. This is the perfect starting point to ignite your fledgling machine learning career and take a HUGE step towards your dream data scientist role."},
+    {
+        "title": "Data Science Hacks, Tips and Tricks",
+        "lessons": "37 Lessons",
+        "description":"The Data Science Hacks, Tips and Tricks course is your one stop destination to become a better and more efficient data scientist! We have poured in our decades of experience with data science and programming (especially Python programming!), to provide you with time-saving hacks related to: Python tips and tricks Data exploration tips and tricks Data preprocessing hacks Efficient use of Jupyter notebooks Python functions Building predictive models"},
+    {
+        "title": "Introduction to Business Analytics",
+        "lessons": "33 Lessons",
+        "description": "With growth in digitisation, Business Analytics is ubiquitous right now. Organizations are splurging to integrate data science solutions in their daily processes. This is where they need Business Analysts. Why pursue Business Analytics: Data is ubiquitous! Organizations need people who can use Business Analytics tools and techniques to make sense of this data. It is one of the hottest field in the industry right now There are so many Business Analytics tools and techniques which can be applied to solve business problems. Keep learning, keep growing! The potential of Business Analytics is limitless - spanning across industries, roles and functions"},
+    {
+        "title": "Introduction to PyTorch for Deep Learning",
+        "lessons": "28 Lessons",
+        "description": "PyTorch was recently voted as the favorite deep learning framework among researchers. It has left TensorFlow behind and continues to be the deep learning framework of choice for many experts and practitioners. PyTorch is super flexible and is quite easy to grasp, even for deep learning beginners. If you work on deep learning and computer vision projects, you’ll love working with PyTorch." },
+    {
+        "title": "Introductory Data Science for Business Managers",
+        "lessons": "4 courses",
+        "description":"Data Science for Managers is a thoughtfully curated program designed especially for decision-makers. Whether you’re a manager, team leader, CxO or entrepreneur, you NEED to be data science educated. And this is the perfect program to get you there. You will get access to three of the most comprehensive courses in this certified program. Enable yourself, and your business, to be ready for the Artificial Intelligence revolution!"},
+    {
+        "title": "Introduction to Natural Language Processing",
+        "lessons": "21 Lessons",
+        "description": "Natural Language Processing (NLP) today powers many key real-life industry applications, such as: Language Translation Dialog Systems / Chatbots Sentiment Analysis Text Summarizers Speech Recognition Autocorrect" },
+    {
+        "title": "Getting started with Decision Trees",
+        "lessons": "20 Lessons",
+        "description": "Introduction to Decision Trees - The course starts with basics of Decision Trees, the philosophy behind decision tree algorithm and why they are so popular among data scientists Terminologies related to decision trees - Don't worry if you don't know anything about Decision Trees - that is the whole point about this course. What is a Leaf Node? Parent Node? Pruning? We will teach you all of these terminologies related to decision tree in a practical manner. Different splitting criterion for decision tree like Gini, chi-square The course teaches you different splitting criteria like Gini, Information Gain, chi-square and how do they impact the decision tree model Implementation of decision tree in Python - The course will tell you several best practices you should keep in mind while implementing Decision Tree algorithm" },
+    {
+        "title": "Introduction to Python",
+        "lessons": "69 Lessons",
+        "description": "Python is a very versatile language since it has a wide array of functionalities already available. The sheer range of functionalities might sound too exhaustive and complicated, you don’t need to be well-versed with them all. Most data scientists have a few go-to libraries for their daily tasks like: for performing data cleaning and analysis - pandas for basic statistical tools – numpy, scipy for data visualization – matplotlib, seaborn"},
+    {
+        "title": "Loan Prediction Practice Problem (Using Python)",
+        "lessons": "16 Lessons",
+        "description": "This course is designed for people who want to solve binary classification problems. Classification is a skill every Data Scientist should be well versed in. In this course, we are solving a real life case study of Dream Housing Finance. The company deals in all home loans. They have a presence across all urban, semi-urban and rural areas. Customers first apply for a home loan after that company validates the customer's eligibility. The company wants to automate the loan eligibility process (real-time) based on customer detail provided while filling online application form. By the end of the course, you will have a solid understanding of Classification problem and Various approaches to solve the probem"   },
+    {
+        "title": "Big Mart Sales Prediction Using R",
+        "lessons": "19 Lessons",
+        "description": "Sales prediction is a very common real life problem that each company faces at least once in its life time. If done correctly, it can have a significant impact on the success and performance of that company. In this course you will be working on the Big Mart Sales Prediction Challenge. The course will equip you with the skills and techniques required to solve regression problems in R. You will be provided with sufficient theory and practice material to hone your predictive modeling skills." },
+    {
+        "title": "Twitter Sentiment Analysis",
+        "lessons": "18 Lessons",
+        "description": "Sentiment Analysis or Opinion Mining is a technique used to analyse the emotion in a text. We can extract the attitude or the opinion of a piece of text and get insights on it. In the context of machine learning, you can think of Sentiment Analysis as a Classification problem where the text can either have a positive sentiment, a negative sentiment or a neutral one."},
+    {
+        "title": "Pandas for Data Analysis in Python",
+        "lessons": "27 Lessons",
+        "description":"The great thing about Pandas is the sheer number of tasks you can perform in Python. It is often called the Swiss Army Knife of data analysis! That should give you a good idea of what you can expect from this powerful library. Here’s a taste of what we’ll cover in this course: Basics of the Pandas library How to import data using Pandas: Read data into Python How to write data using Pandas Perform data analysis and manipulation using Pandas: Select columns and rows in Pandas Manipulate columns in Pandas - Rename columns, sort data in Pandas dataframe, binning data using Pandas, etc. How to deal with missing values using Pandas What is the Apply function in Pandas and how you can use it Aggregate data in Pandas - a very handy tool for quick data analysis How to merge and join multiple Pandas dataframes Pivot tables in Pandas (yes, you can draw up pivot tables in Python using Pandas!) And we have even included an illustrated Pandas cheatsheet just for you!" },
+    {
+        "title": "Support Vector Machine (SVM) in Python and R",
+        "lessons": "13 Lessons",
+        "description":  "This free course will not only teach you basics of Support Vector Machines (SVM) and how it works, it will also tell you how to implement it in Python and R. This course on SVM would help you understand hyperplanes and Kernel tricks to leave you with one of the most popular machine learning algorithms at your disposal."  },
+    {
+        "title": "Evaluation Metrics for Machine Learning Models",
+        "lessons": "25 Lessons",
+        "description": "Evaluation metrics, essentially, explain the performance of a machine learning model. An important aspect of evaluation metrics is their capability to discriminate among model results. If you’ve ever wondered how concepts like AUC-ROC, F1 Score, Gini Index, Root Mean Square Error (RMSE), and Confusion Matrix work, well - you’ve come to the right course!"},
+    {
+        "title": "Fundamentals of Regression Analysis",
+        "lessons": "24 Lessons",
+        "description": "The truth, as always, lies somewhere in between. There are multiple types of regression apart from linear regression: Ridge regression Lasso regression Polynomial regression Stepwise regression, among others. Linear regression is just one part of the regression analysis umbrella. Each regression form has its own importance and a specific condition where they are best suited to apply. Regression analysis marks the first step in predictive modeling. The different types of regression techniques are widely popular because they’re easy to understand and implement using a programming language of your choice." },
+    {
+        "title": "Getting Started with scikit-learn (sklearn) for Machine Learning",
+        "lessons": "27 Lessons",
+        "description": "Scikit-learn, or sklearn for short, is the first Python library we turn to when building machine learning models. Sklearn is unanimously the favorite Python library among data scientists. As a newcomer to machine learning, you should be comfortable with sklearn and how to build ML models, including: Linear Regression using sklearn Logistic Regression using sklearn, and so on. There’s no question - scikit-learn provides handy tools with easy-to-read syntax. Among the pantheon of popular Python libraries, scikit-learn (sklearn) ranks in the top echelon along with Pandas and NumPy."},
+    {
+        "title": "Convolutional Neural Networks (CNN) from Scratch",
+        "lessons": "17 Lessons",
+        "description": "Convolutional Neural Networks, or CNN as they’re popularly called, are the go-to deep learning architecture for computer vision tasks, such as object detection, image segmentation, facial recognition, among others. CNNs have even been extended to the field of video analysis! If you are picking one deep learning architecture to learn and are not sure where to start, you should go for convolutional neural networks. Deep learning enthusiasts and experts with CNN knowledge are being widely sourced in the industry." },
+    {
+        "title": "Dimensionality Reduction for Machine Learning",
+        "lessons": "23 Lessons",
+        "description": "Every data scientist, aspiring established, should be aware of the different dimensionality reduction techniques, such as Principal Component Analysis (PCA), Factor Analysis, t-SNE, High Correlation Filter, Missing Value Ratio, among others. So in this beginner-friendly course, you will learn the basics of dimensionality reduction and why you should know dimensionality reduction in machine learning. We will also cover 12 dimensionality reduction techniques! This course is as comprehensive an introduction as you can get!"},
+    {
+        "title": "K-Nearest Neighbors (KNN) Algorithm in Python and R",
+        "lessons": "10 Lessons",
+        "description":  "K-Nearest Neighbor (KNN) is one of the most popular machine learning algorithms. As a newcomer or beginner in machine learning, you’ll find KNN to be among the easiest algorithms to pick up. And despite its simplicity, KNN has proven to be incredibly effective at certain tasks in machine learning. The KNN algorithm is simple to understand, easy to explain and perfect to demonstrate to a non-technical audience (that’s why stakeholders love it!). That’s a key reason why it’s widely used in the industry and why you should know how the algorithm works."  },
+    {
+        "title": "Ensemble Learning and Ensemble Learning Techniques",
+        "lessons": "37 Lessons",
+        "description": "Ensemble learning is a powerful machine learning algorithm that is used across industries by data science experts. The beauty of ensemble learning techniques is that they combine the predictions of multiple machine learning models. You must have used or come across several of these ensemble learning techniques in your machine learning journey: - Bagging - Boosting - Stacking - Blending, etc. These ensemble learning techniques include popular machine learning algorithms such as XGBoost, Gradient Boosting, among others. You must be getting a good idea of how vast and useful ensemble learning can be!" },
+    {
+        "title": "Linear Programming for Data Science Professionals",
+        "lessons": "20 Lessons",
+        "description": "We are solving optimization problems everyday - without realizing it. Think of how you distributed the chocolate among your peers or siblings - that’s your way of optimizing the situation. On the other hand devising inventory and warehousing strategy for an e-tailer can be very complex. Millions of SKUs with different popularity in different regions to be delivered in defined time and resources. And linear programming helps us solve these optimization problems with ease and efficiency. As a data science professional, you are bound to come across these optimization problems that you will solve using linear programming. Simply put, you should know what linear programming is, and the different methods to solve linear programming problems." },
+    {
+        "title": "Naive Bayes from Scratch",
+        "lessons": "19 Lessons",
+        "description":  "Naive Bayes ranks in the top echelons of the machine learning algorithms pantheon. It is a popular and widely used machine learning algorithm and is often the go-to technique when dealing with classification problems. The beauty of Naive Bayes lies in it’s incredible speed. You’ll soon see how fast the Naive Bayes algorithm works as compared to other classification algorithms. It works on the Bayes theorem of probability to predict the class of unknown datasets. You’ll learn all about this inside the course! So whether you’re trying to solve a classic HR analytics problem like predicting who gets promoted, or you’re aiming to predict loan default - the Naive Bayes algorithm will get you on your way."},
+    {
+        "title": "Learn Swift for Data Science",
+        "lessons": "21 Lessons",
+        "description":"In this free course on Swift for Data Science, we will learn about Swift as a programming language and how it fits into the data science space. If you’re a Python user, you’ll notice the subtle differences and the incredible similarities between the two. We showcase Swift code as well in the course so get started!"
+    },
+    {
+        "title": "Introduction to Web Scraping using Python",
+        "lessons": "13 Lessons",
+        "description":  "But there might be occasions when you need to collect data from a website that does not provide a specific API. This is where having the ability to perform web scraping comes in handy. As a data scientist, you can code a simple Python script and extract the data you’re looking for. So knowing how to perform web scraping using Python will help you go a long way towards becoming a resourceful data scientist. Are you ready to take the next step and dive in? A note of caution here – web scraping is subject to a lot of guidelines and rules. Not every website allows the user to scrape content so there are certain legal restrictions at play. Always ensure you read the website’s terms and conditions on web scraping before you attempt to do it. In this course, we will dive into the basics of web scraping using Python. We will understand what web scraping is, the different Python libraries for performing web scraping, and finally we’ll implement web scraping using Python in a real-world project. There’s a lot to unpack here so enroll today and start learning!"  },
+    {
+        "title": "Tableau for Beginners",
+        "lessons": "17 Lessons",
+        "description":"Tableau is the gold standard in business intelligence, analytics and data visualization tools. Tableau Desktop (and now Tableau Public) have transformed the way we interact with visualizations and tell data stories to our clients, stakeholders, and to non-technical audiences around the world. Tableau has been recognized as a Leader in the Gartner Magic Quadrant for Analytics and Business Intelligence Platforms for 8 straight years. Here’s Gartner’s most recent ranking in 2020: In this Tableau for Beginners course, you will learn everything you need to get started with this wonderful visualization and business intelligence tool. You’ll be able to build charts like bar charts, line charts (for working with time series data), pie charts, and even get the hang of geospatial analysis using map visualizations in Tableau!"},
+    {
+        "title": "Getting Started with Neural Networks",
+        "lessons": "45 Lessons",
+        "description": "Do you want to acquire a super power? How about learning neural networks? Neural networks are at the heart of the deep learning revolution that’s happening around us right now. Neural networks are the present and the future. The different neural network architectures like convolutional neural networks (CNN), recurrent neural networks (RNN), and others have altered the deep learning landscape."},
+    {
+        "title": "Introduction to AI & ML",
+        "lessons": "17 Lessons",
+        "description":  "Artificial Intelligence and Machine Learning have become the centerpiece of strategic decision making for organizations. They are disrupting the way industries and roles function - from sales and marketing to finance and HR, companies are betting big on AI and ML to give them a competitive edge. And this, of course, directly translates to their hiring. Thousands of vacancies are open as organizations scour the world for AI and ML talent. There hasn’t been a better time to get into this field!"},
+    {
+        "title": "Winning Data Science Hackathons - Learn from Elite Data Scientists",
+        "lessons": "7 Lessons",
+        "description":   "This course is an amalgamation of various talks by top data scientists and machine learning hackers, experts, practitioners, and leaders who have participated and won dozens of hackathons. They have already gone through the entire learning process and they showcase their work and thought process in these talks. This course features top data science hackers and experts, including Sudalai Rajkumar (SRK), Dipanjan Sarkar, Rohan Rao, Kiran R and many more! From effective feature engineering to choosing the right validation strategy, there is a LOT to learn from this course so get started today!"},
+    {
+        "title": "Hypothesis Testing for Data Science and Analytics",
+        "lessons": "19 Lessons",
+        "description":"Fundamentals of Hypothesis Testing: The course begins with a simple-to-understand example on hypothesis testing. This chapter will clear all your basics like - Null Hypothesis, Alternative Hypothesis, Type 1 Error, Type 2 Error, and Significance Level. p-value What is the Z Test? The course introduces the most basic type of testing a hypothesis - Z test. Z tests are a statistical way of testing. The chapter covers the one sample as well as the two sample Z test. What is the t-Test? The t-test is another test for validating the hypothesis. The chapter begins with a unique example and later covers both the one-sample and two-sample t-test. Deciding between the Z Test and t-Test Are you confused on how to use these tests? Don’t worry, the course comprises a simple step-by-step guide on choosing the best test for your experiment. Case Study: Hypothesis Testing for Coronavirus in Python You’ll get to put your theoretical knowledge into practice and see how well you can do. You will get to work on a hypothesis testing case study on the corona virus dataset in Python!"}
+]

scraping.ipynb

@@ -0,0 +1,104 @@
+{
+  "nbformat": 4,
+  "nbformat_minor": 0,
+  "metadata": {
+    "colab": {
+      "provenance": []
+    },
+    "kernelspec": {
+      "name": "python3",
+      "display_name": "Python 3"
+    },
+    "language_info": {
+      "name": "python"
+    }
+  },
+  "cells": [
+    {
+      "cell_type": "code",
+      "execution_count": 1,
+      "metadata": {
+        "id": "4AuMIyZkmokI"
+      },
+      "outputs": [],
+      "source": [
+        "import requests\n",
+        "from bs4 import BeautifulSoup\n",
+        "import json"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "import requests\n",
+        "from bs4 import BeautifulSoup\n",
+        "import json\n",
+        "\n",
+        "base_url = \"https://courses.analyticsvidhya.com/collections\"\n",
+        "courses = []\n",
+        "page = 1\n",
+        "\n",
+        "while True:\n",
+        "    url = f\"{base_url}?page={page}\" if page > 1 else base_url\n",
+        "    response = requests.get(url)\n",
+        "\n",
+        "    if response.status_code != 200:\n",
+        "        print(f\"Stopped at page {page}, no more pages or error.\")\n",
+        "        break\n",
+        "\n",
+        "    soup = BeautifulSoup(response.content, 'html.parser')\n",
+        "    course_cards = soup.find_all(\"div\", class_=\"course-card__body\")\n",
+        "    if not course_cards:\n",
+        "        print(f\"Stopped at page {page}, no course cards found.\")\n",
+        "        break\n",
+        "\n",
+        "    for course_card in course_cards:\n",
+        "        title_tag = course_card.find(\"h3\")\n",
+        "        title = title_tag.get_text(strip=True) if title_tag else \"Title not found\"\n",
+        "\n",
+        "        footer_tag = course_card.find_next_sibling(\"footer\")\n",
+        "        lesson_tag = footer_tag.find(\"span\", class_=\"course-card__lesson-count\") if footer_tag else None\n",
+        "        lesson_count = lesson_tag.get_text(strip=True) if lesson_tag else \"Lesson count not found\"\n",
+        "\n",
+        "        courses.append({\n",
+        "            \"title\": title,\n",
+        "            \"lessons\": lesson_count\n",
+        "        })\n",
+        "\n",
+        "    print(f\"Scraped page {page} successfully.\")\n",
+        "    page += 1\n",
+        "with open(\"free_courses.json\", \"w\", encoding=\"utf-8\") as file:\n",
+        "    json.dump(courses, file, ensure_ascii=False, indent=4)\n",
+        "\n",
+        "print(\"Scraped data saved to free_courses.json\")\n"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "bZsP9ZRbuDBF",
+        "outputId": "6be5b9b3-5348-4f95-bd4d-f80ab48bf3b1"
+      },
+      "execution_count": 5,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "Scraped page 1 successfully.\n",
+            "Scraped page 2 successfully.\n",
+            "Scraped page 3 successfully.\n",
+            "Scraped page 4 successfully.\n",
+            "Scraped page 5 successfully.\n",
+            "Scraped page 6 successfully.\n",
+            "Scraped page 7 successfully.\n",
+            "Scraped page 8 successfully.\n",
+            "Scraped page 9 successfully.\n",
+            "Stopped at page 10, no course cards found.\n",
+            "Scraped data saved to free_courses.json\n"
+          ]
+        }
+      ]
+    }
+  ]
+}