// 80 courses indexed
The course directory
Every course we track across 10+ providers, in one searchable index. Want a shortlist picked for your goals? Run a free skill gap analysis.
Mastering Python Programming: Apply, Analyze, and Build
Take your Python programming skills beyond basic syntax by learning how to design modular, reusable, and efficient applications using functional programming and object-oriented programming principles. This course explores how to build scalable Python solutions through functions, recursion, classes, inheritance, exception handling, and advanced object-oriented features. You'll begin by designing reusable functions, managing parameters, and solving structured problems with Python data structures. As you progress, you'll analyze recursion, functional programming patterns, and variable scope befo
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Understand RAG Basics
"Understand RAG Basics" is an intermediate course for developers and data scientists who want to build more powerful and trustworthy AI applications. While Large Language Models (LLMs) are revolutionary, they often lack specific, up-to-date knowledge and can hallucinate answers. This 2-hour course provides the fundamental solution: Retrieval-Augmented Generation (RAG). You will need to be familiar with basic Python, API, and LLMs. You will also need Python and a code editor like VS Code installed locally. Focused on practical application, this course transitions from theory to execution. Y
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Foundations of Data Science: K-Means Clustering in Python
Organisations all around the world are using data to predict behaviours and extract valuable real-world insights to inform decisions. Managing and analysing big data has become an essential part of modern finance, retail, marketing, social science, development and research, medicine and government. This MOOC, designed by an academic team from Goldsmiths, University of London, will quickly introduce you to the core concepts of Data Science to prepare you for intermediate and advanced Data Science courses. It focuses on the basic mathematics, statistics and programming skills that are necessary
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Applied Fundamentals: Hangman
This course features Coursera Coach! A smarter way to learn with interactive, real-time conversations that help you test your knowledge, challenge assumptions, and deepen your understanding as you progress through the course. This course is designed to provide a hands-on approach to developing a simple Hangman game using Python. You will gain practical experience by building the game step by step while learning key concepts in Python programming. By the end of the course, you will have developed a working Hangman game, built upon a strong foundation of Python syntax, functions, and logic. Th
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Embed Everything
Embed Everything is an intermediate-level course designed for machine learning practitioners and Python developers who want to master the art of converting unstructured data into powerful numerical representations. In a world where data is king, its value is often locked away in complex formats like product descriptions, images, and documents. This course provides the key to unlocking that value. You will learn to build a complete, scalable embedding pipeline from the ground up. Through practical, hands-on labs and expert-led video lessons, you'll apply state-of-the-art pre-trained models to
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Introduction to Python
Learning Python gives the programmer a wide variety of career paths to choose from. Python is an open-source (free) programming language that is used in web programming, data science, artificial intelligence, and many scientific applications. Learning Python allows the programmer to focus on solving problems, rather than focusing on syntax. Its relative size and simplified syntax give it an edge over languages like Java and C++, yet the abundance of libraries gives it the power needed to accomplish great things. In this tutorial you will create a guessing game application that pits the comput
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Big O notation: Python to Rust
Big O notation: Python to Rust is a hands-on algorithmic complexity course for engineers transitioning from Python to Rust who want to reason rigorously about how their code scales. You will learn Big O, Big Theta, and Big Omega notation; analyze the time and space complexity of common operations on Python and Rust data structures (list/Vec, dict/HashMap, set/HashSet, tuple, slice, BTreeMap); and compare measured performance in both languages on identical workloads. The course covers amortized analysis, recursion and master theorem, worst case versus expected case, the cost of allocation and b
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Python Programming for Quantum Computing
Updated in May 2025. This course now features Coursera Coach! A smarter way to learn with interactive, real-time conversations that help you test your knowledge, challenge assumptions, and deepen your understanding as you progress through the course. This course is designed to provide a solid foundation in Python programming, tailored for individuals interested in quantum computing. The first section begins with an introduction to Python from scratch, walking you through the installation of Anaconda on both Windows and macOS, followed by an overview of Python’s core concepts. You’ll learn
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AI Workflow: Business Priorities and Data Ingestion
This is the first course of a six part specialization. You are STRONGLY encouraged to complete these courses in order as they are not individual independent courses, but part of a workflow where each course builds on the previous ones. This first course in the IBM AI Enterprise Workflow Certification specialization introduces you to the scope of the specialization and prerequisites. Specifically, the courses in this specialization are meant for practicing data scientists who are knowledgeable about probability, statistics, linear algebra, and Python tooling for data science and machine lear
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Production Deployment and Advanced Patterns
The Production Deployment and Advanced Patterns course is designed for developers, engineers, and technical product builders who are new to Generative AI but already possess intermediate programming knowledge, basic Python proficiency, and familiarity with development tools and APIs, and who want to build, deploy, and scale AI-powered agents in real-world applications. The course equips learners with the skills to transform AI agents into professional-grade applications ready for real-world use. Starting with user interface development, learners build interactive agent interfaces using Stream
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Matplotlib with Python: E-commerce Data Visualization
Matplotlib E-commerce Data Visualization with Python is an intermediate-level course that teaches you how to analyze e-commerce datasets and create meaningful visualizations using Python and Matplotlib. Through a practical case study, you will build the skills to set up your analysis environment, prepare data, and transform raw business data into clear visual insights. You will begin by installing and configuring Anaconda and Matplotlib, exploring dataset characteristics, identifying unique values, and preparing data for analysis. Next, you will learn the fundamentals of Matplotlib, including
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Hands-On Blockchain for Python Developers
This course will help Python developers enhance their productivity in writing DeFi and NFT applications. You'll gain in-depth knowledge of related technologies such as Layer 2 and IPFS, further expanding your understanding of the blockchain ecosystem. This course equips learners with the skills to build real-world blockchain applications using Vyper and web3.py. It covers essential tools like Ape Framework and explores key technologies such as Layer 2 and IPFS. Designed for developers, it provides hands-on experience in creating decentralized exchanges, NFT marketplaces, and more. This cours
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Production Governance and MLOps on Databricks
This intermediate course provides a practical, hands-on exploration of Databricks Governance, focusing on the essential tools and workflows for managing and securing your data lakehouse. You will learn to navigate and control access to your data assets using Unity Catalog, the foundation of Databricks governance. The course covers the core hierarchy of metastores, catalogs, schemas, and tables, and teaches you how to manage them programmatically using the Databricks Python SDK, CLI, and VS Code extension. Beyond foundational access control, you will master the skills to implement modern CI/CD
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Use the Standard Library
Unlock the full potential of Python through its powerful Standard Library. This course takes you on a comprehensive journey, helping you understand how to leverage Python's built-in tools and modules to make your programming more efficient and effective. You'll dive into modules like os, datetime, math, sys, and random, exploring essential functions, and learning how to manage files, dates, times, and more in Python. You will start by gaining an overview of the Standard Library and how to import modules, followed by detailed lessons on practical modules that are commonly used in everyday prog
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Data Analysis and Visualization
By the end of this course, learners are provided a high-level overview of data analysis and visualization tools, and are prepared to discuss best practices and develop an ensuing action plan that addresses key discoveries. It begins with common hurdles that obstruct adoption of a data-driven culture before introducing data analysis tools (R software, Minitab, MATLAB, and Python). Deeper examination is spent on statistical process control (SPC), which is a method for studying variation over time. The course also addresses do’s and don’ts of presenting data visually, visualization software (Tabl
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AI Agents with Model Context Protocol
Build AI Agents That Actually Work AI agents are everywhere—but most of them fail in frustrating, unpredictable ways. They get confused, waste tokens, hit dead ends, and require constant babysitting. This course teaches you the patterns and architectures that separate agents that struggle from agents that succeed. Using Python and the Model Context Protocol (MCP), you'll learn to build AI agents from the ground up—and more importantly, you'll learn why certain designs work while others fall apart. What You'll Learn: - Build MCP Tool Servers — Create the bridge that lets AI agents interact
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Design Thinking and Predictive Analytics for Data Products
This is the second course in the four-course specialization Python Data Products for Predictive Analytics, building on the data processing covered in Course 1 and introducing the basics of designing predictive models in Python. In this course, you will understand the fundamental concepts of statistical learning and learn various methods of building predictive models. At each step in the specialization, you will gain hands-on experience in data manipulation and building your skills, eventually culminating in a capstone project encompassing all the concepts taught in the specialization.
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Build Serverless Automation with AWS Lambda
Learners will understand, implement, and evaluate a real-world serverless automation workflow using AWS Lambda, API Gateway, and Amazon S3. By the end of this course, learners will be able to design API-driven backend solutions, implement GET and PUT operations using Python, and automate data processing in a scalable cloud environment. This course benefits learners by providing hands-on exposure to a practical DevOps case study rather than isolated service tutorials. Learners gain clarity on how AWS services interact in real production-like scenarios, strengthening their ability to build, tro
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Principles of Computing (Part 1)
This two-part course builds upon the programming skills that you learned in our Introduction to Interactive Programming in Python course. We will augment those skills with both important programming practices and critical mathematical problem solving skills. These skills underlie larger scale computational problem solving and programming. The main focus of the class will be programming weekly mini-projects in Python that build upon the mathematical and programming principles that are taught in the class. To keep the class fun and engaging, many of the projects will involve working with strat
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Problem Solving, Python Programming, and Video Games
This course is an introduction to computer science and programming in Python. Upon successful completion of this course, you will be able to: 1. Take a new computational problem and solve it, using several problem solving techniques including abstraction and problem decomposition. 2. Follow a design creation process that includes: descriptions, test plans, and algorithms. 3. Code, test, and debug a program in Python, based on your design. Important computer science concepts such as problem solving (computational thinking), problem decomposition, algorithms, abstraction, and software qual
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Streaming Data Pipelines with Kafka and Spark
Build practical expertise in real-time data engineering using Apache Kafka, Apache Spark, Spark Structured Streaming, PySpark, Python, Docker, and Docker Compose. You will learn how data engineers design, process, monitor, and maintain streaming pipelines that continuously move event data from source systems to reliable downstream outputs. You will begin by exploring event streaming fundamentals and the architecture of Apache Kafka. You will examine brokers, topics, partitions, producers, consumers, offsets, consumer groups, message ordering, and delivery behavior. Through guided demonstratio
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Advanced Machine Learning and its Applications
The third course introduces advanced machine learning techniques and their applications. This course is built on the Applied AI Foundations Specialization, which introduced the fundamentals of machine learning, and Course 1, which developed LLM-empowered Python programming skills for AI. In this course, advanced data preprocessing, machine learning outcome evaluation, neural network design and optimization, deep learning, and generative artificial intelligence are introduced. Since these techniques underpin essential modern AI systems in science and engineering, after completing this course, y
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Data Visualization with ChatGPT: Python for Dashboarding
In this 1-hour long project-based course, you will explore the integration of ChatGPT-generated code into interactive Streamlit applications for data analysis and visualization. We will achieve this by working on a hands-on project where you'll use ChatGPT to analyze and interpret data, develop visualization through Python libraries, and incorporate this into a Streamlit app to create a dynamic, user-friendly dashboard. ChatGPT and Streamlit represent a powerful combination for developing data-driven applications. ChatGPT, with its advanced language understanding and code generation capabilit
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Analyze Video Data Using OpenCV and Python
By the end of this course, learners will be able to analyze video data, apply color models, implement image preprocessing techniques, and build object detection and tracking solutions using OpenCV and Python. They will gain the ability to process real-time and recorded video streams, extract meaningful visual features, and apply motion analysis algorithms to solve practical computer vision problems. This course benefits learners by providing a structured, hands-on pathway from foundational concepts to advanced video analytics techniques. Learners will develop industry-relevant skills in image
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