Company
Courses and full video lessons from CodeSignal.
62 courses
CodeSignal
Build core artificial intelligence and machine learning algorithms from scratch to understand how they work beneath high-level libraries. This advanced path covers neural networks, clustering, ensembles, optimization, classification, and regression.
CodeSignal
Build intermediate Python skills in core algorithms and data structures used in technical interviews. Learn how to choose, implement, analyze, and explain common approaches to graph, tree, list, hashing, sorting, and searching problems.
CodeSignal
Learn the basics of working with an agentic coding assistant in the terminal. Practice configuring projects, managing context, using planning workflows, and extending capabilities with reusable skills.
CodeSignal
Build a practical foundation in machine learning with scikit-learn, from data preprocessing to model training and evaluation. Explore regression, classification, ensembles, cross-validation, and hyperparameter tuning.
CodeSignal
Build practical data science skills in Python through hands-on work with NumPy, Pandas, visualization, preprocessing, and machine learning. Analyze real datasets while learning how to prepare data, model outcomes, and interpret patterns.
CodeSignal
Learn the foundations of Python programming, from writing your first program to using functions, loops, conditionals, and simple data structures. This beginner-friendly path helps you build practical coding skills step by step.
CodeSignal
Build foundational generative AI skills for workplace communication. Learn to write effective prompts, create and edit images, and evaluate AI-generated outputs.
CodeSignal
Build Claude-powered agents in Python using direct API calls, tool integration, workflow orchestration, and asynchronous execution. Learn to design multi-agent systems without relying on agent frameworks.
CodeSignal
Build beginner-level data analysis skills with Python by learning how to clean, transform, analyze, and visualize data. Practice using libraries such as NumPy, pandas, Matplotlib, Seaborn, and SciPy to work with real datasets.
CodeSignal
Build a practical foundation in generative AI for everyday work, communication, and content creation. Learn how to use AI tools for text, images, voice, video, and professional productivity tasks.
CodeSignal
Explore the ethical foundations, risks, and governance practices needed to develop and evaluate AI systems responsibly. This beginner-friendly path covers privacy, bias, accountability, transparency, and future AI challenges.
CodeSignal
Deepen your Python data analysis skills with NumPy and Pandas, from array operations to advanced DataFrame transformations. Learn to clean, reshape, merge, and analyze datasets using practical workflows.
CodeSignal
Learn to use an AI coding assistant and Python to create clear, reusable data visualizations. Progress from basic plots to real-world analysis, interactive dashboards, and automated visualization workflows.
CodeSignal
Build secure and reliable web APIs with Python and FastAPI. Learn endpoint creation, request handling, data validation, error management, and JWT authentication.
CodeSignal
Learn to build AI agents that use custom tools, retrieval workflows, and multi-agent collaboration. This intermediate path moves from foundational chat assistants to systems that can automate more complex tasks.
CodeSignal
Learn the fundamentals of prompt engineering for working with large language models. Practice writing prompts that guide text generation, formatting, revision, and response length.
CodeSignal
Learn an advanced specification-driven approach to API development using AI-assisted planning, task decomposition, and execution workflows. Build skills for turning product requirements into implementation-ready tasks and production-quality features.
CodeSignal
Build a practical foundation in natural language processing using Python. Learn to explore, preprocess, vectorize, and classify text data with common machine learning techniques.
CodeSignal
Learn to build Python-based MCP servers that let AI agents use tools, access data, and take action across services. This intermediate path covers server development, agent integration, transport options, caching, web integration, and authentication.
CodeSignal
Learn how to use OpenCode, an open-source AI coding agent for the terminal, to inspect codebases, edit files, run commands, and support real development workflows. This beginner path covers setup, configuration, project work, testing, refactoring, and automation practices.
