// 57 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.
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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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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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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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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Agile Software Development with Python: TDD and BDD
In today’s fast-moving tech world, great developers do more than just write code — they build adaptable, high-quality software that meets real user needs. This hands-on course will guide you through the essential tools and mindsets that power modern software teams. You’ll gain a deep understanding of Agile principles and the Scrum framework, learning how to iterate quickly and deliver value efficiently. Through practical Python exercises, you’ll master Test-Driven Development (TDD) and Behavior-Driven Development (BDD) — industry-proven practices that help you design cleaner, more reliable, an
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Create Your First Web App with Python and Flask
In this 2-hour long project-based course, you will learn the basics of web application development with Python using the Flask framework. Through hands on, practical experience, you will go through concepts like creating a Flask Application, using Templates in Flask Applications, using SQLAlchemy and SQLite with Flask, and using Flask and WTForms. You will then apply the concepts to create your first web application with Python and Flask. This course is aimed at learners who are looking to get started with web application development using Python, and have some prior programming experience in
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Gen AI for Code Generation for Python
The Gen AI for Code Generation for Python course introduces practical techniques for using Generative AI to create Python code efficiently. This course is designed to help learners understand how AI tools can assist in writing everything from simple Python scripts to complete end-to-end applications. You will explore key methods for AI-assisted code generation, apply prompt strategies, and learn how to streamline development using generative models. By the course's conclusion, you will be able to: - Generate code with the help of the Generative AI tool - Implement strategies to design pre
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Optimize TensorFlow Models For Deployment with TensorRT
This is a hands-on, guided project on optimizing your TensorFlow models for inference with NVIDIA's TensorRT. By the end of this 1.5 hour long project, you will be able to optimize Tensorflow models using the TensorFlow integration of NVIDIA's TensorRT (TF-TRT), use TF-TRT to optimize several deep learning models at FP32, FP16, and INT8 precision, and observe how tuning TF-TRT parameters affects performance and inference throughput. Prerequisites: In order to successfully complete this project, you should be competent in Python programming, understand deep learning and what inference is, and
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Forecast Business Metrics: Uncover Value Drivers
In this short, practical course, you’ll learn how to use supervised learning to forecast key business metrics and uncover the drivers that shape performance. Through hands-on exercises in Python, you’ll build and tune regression and gradient-boosted models to predict outcomes such as next-quarter EBITDA. Then, you’ll apply explainable AI techniques, including SHAP and feature importance, to translate model outputs into clear, actionable business insights. By the end of the course, you’ll be able to evaluate forecast accuracy, identify which variables truly drive results, and communicate your f
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Hands-on Python for Networking Professionals
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. In this course, you will learn how to leverage Python to automate and simplify tasks within the field of networking. You will gain hands-on experience with tools and scripts that streamline common networking tasks such as error handling, environment variable management, and remote system interactions. By using Python, you can scale your network management, improve repro
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Intro to Python: File Processing and Exception Handling
To round out your introduction to programming with Python, in this course, you'll manage files and directories through code. You'll also perform basic exception handling to gracefully address issues in your code. This is the third and final course in a multi-course Specialization. All of the courses in this Specialization require that you use the provided virtual machine, which includes an installation of Python. The course setup instructions provided in the first course go into more detail about the hardware and software requirements.
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Analyze Financial Data with Python for Decision Making
Learners will apply Python programming to analyze financial data, interpret time-based trends, build regression models, and communicate insights through effective visualizations. By the end of this course, learners will be able to transform raw financial datasets into meaningful analytical outputs that support data-driven financial decisions. This course is designed to bridge the gap between Python programming and practical financial analytics. Learners gain hands-on experience with Python setup, essential libraries, DataFrame operations, and core analytical techniques before progressing to f
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Select Topics in Python: Django
Code and run Django websites without installing anything! This course is designed for learners who have some experience with Python but a novice to Django. The modules in this course cover setting up a Django project; understanding the relationship between views, templates, and URL patterns; introduces models and the database; styling with Bootstrap; and deploying Django. To allow for a truly hands-on, self-paced learning experience, this course is video-free. Assignments contain short explanations with images and runnable code examples with suggested edits to explore code examples further,
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Python for Everybody Specialization
University of Michigan's beginner-friendly path covering Python programming, data structures, web data, and databases.
Beginner