Courses from 1000+ universities
Buried in Coursera’s 300-page prospectus: two failed merger attempts, competing bidders, a rogue shareholder, and a combined market cap that shrank from $3.8 billion to $1.7 billion.
600 Free Google Certifications
Aprender
Marketing in a Digital World
The Ancient Greeks
Organize and share your learning with Class Central Lists.
View our Lists Showcase
Discover how Model Context Protocol (MCP) standardizes context provision to LLMs, functioning like a USB-C port for AI applications by connecting models to various data sources and tools.
Explore the fundamentals of Web 3.0, including mining, cryptocurrencies, data sharing, smart contracts, tokenomics, and the metaverse in this comprehensive breakdown with industry expert Pareen Lathia.
Comprehensive guide to building AI applications with LangChain, covering chatbots, RAG pipelines, and integration with various tools and platforms for generative AI development.
Explore the distinctions between generative AI, agentic AI, and AI agents, focusing on how agentic AI operates autonomously to solve complex problems in real-time.
Learn SQL constraints including Not Null, Unique, and Primary Key to ensure data accuracy and reliability in MySQL databases. Practical examples and implementation techniques provided.
Explore blockchain technology fundamentals, including its structure, key players, transaction processes, and core concepts like hash keys and memory pools.
Comprehensive overview of feature transformation techniques in machine learning, covering standardization, scaling, MinMax, Robust Scalar, and Gaussian transformations for data preprocessing.
Explore EvalML, an AutoML library automating feature engineering, selection, model creation, and tuning. Learn to streamline your data science workflow and improve project efficiency.
Explore polynomial kernels in SVM, understanding their intuition, use cases, and hyperparameter tuning for enhanced machine learning model performance.
Explore incremental machine learning model training for continuous updates, addressing model drift and improving performance over time.
In-depth exploration of AlexNet architecture, including mathematical operations, layers, and implementation code for advanced deep learning and convolutional neural networks.
Learn to troubleshoot and debug Heroku applications, focusing on log analysis and error resolution for web and data science projects.
Learn to build a fake news classifier using machine learning and NLP techniques. Covers data preprocessing, feature extraction, and multinomial classification algorithms for detecting misinformation.
Gain in-depth intuition on LSTM Recurrent Neural Networks, exploring memory cells, operations, and layers for advanced understanding of this powerful deep learning architecture.
Learn to query MongoDB with Python, focusing on JSON documents and data science applications. Covers server connection, insertion, querying, operators, and nested documents.
Get personalized course recommendations, track subjects and courses with reminders, and more.