From tokens to transformers — understand ChatGPT, build RAG pipelines, and master prompt engineering.
From localhost to 10K concurrent users — master the engineering behind production-grade systems.
Master problem-solving through visual algorithms — no coding required, just pure thinking.
This path is built for aspiring data scientists and AI engineers who want the full skill stack in one structured program. It covers data science workflows, database management, Python programming, and data structures and algorithms as the foundation, then moves into exploratory data analysis, statistics, and data visualization. From there, you go deep into machine learning, covering supervised and unsupervised methods, model evaluation, and hyperparameter tuning, followed by deep learning, natural language processing, and current large language models and generative AI. By the end, you will have a working grasp of AI-driven solutions ready for real applications, not isolated topics learned in silos. A strong option for anyone serious about a data science or AI.
This path is built for aspiring data engineers who need to manage, process, and analyze large-scale data efficiently. It covers Big Data fundamentals, database management across SQL and NoSQL, Python programming, and data structures and algorithms as the base layer for everything else. From there, you move into machine learning and deep learning basics built specifically for data engineering use cases, then into Big Data technologies like Apache Spark and Kafka for real-time and batch processing at scale. The path is structured with hands-on, real-world exercises rather than pure theory. Whether you are new to the field or sharpening existing skills, this program gives a complete roadmap covering the tools teams actually rely on daily.
This path is built for aspiring data analysts who want a complete route from fundamentals to applied machine learning. It starts with core data concepts and database management, then builds Python skills, data structures and algorithms, and statistics fundamentals specific to analysis work. From there, you apply machine learning to analytical problems, get a basic introduction to deep learning, and finish with Power BI for business intelligence and reporting. Throughout, the focus stays on analyzing, visualizing, and interpreting data with real-world exercises rather than abstract theory alone. Suited for beginners building a first analytics skill set as well as working analysts who want to formalize and extend what they already know into a stronger profile.
This is the Starter Tier for Python programming, a short, self-contained entry point for anyone new to coding. It gets you writing and running Python quickly, without the time commitment of a full course, so you can confirm whether programming is the right direction before going further. There are no labs, projects, or live sessions at this level, keeping the barrier to starting as low as possible. It works best as a first step before moving into Tier 2 for structured foundations, Tier 3 for guided labs, or higher tiers with projects and instructor support. If you are unsure whether you want to commit to learning Python seriously, this tier is built to answer that question fast, with minimal setup and no upfront cost of time or money.
This self-guided tier covers the foundations of Python programming across 3 days, roughly 9 hours total. You will work through Python basics and control flow, data structures and functions, and file handling with modules, with hands-on exercises after each topic covered. Each day ends with a coding quiz, and a final assessment after Day 3 unlocks your Foundations of Python Programming certificate. There are no live labs or instructor sessions at this level, so it fits people who learn well independently and want a structured, paced path rather than an open-ended tutorial. A solid step up from Tier 1 for anyone ready to commit real time to building an actual foundation instead of just sampling the basics casually.
This tier extends the foundations into 5 days of hands-on labs, about 15 hours total, with an AI chatbot mentor guiding you through real coding scenarios. Labs cover Python basics practice, data structure operations, file handling and error management, external libraries, and a mini project building a command-line to-do list from scratch. After each lab, you get small challenges like building a password generator or refactoring code to use functions more cleanly. A live doubt-clearing session is included, and the chatbot mentor helps troubleshoot syntax errors and suggests more efficient ways to write code along the way. Built for people who learn best by doing, with enough support built in that getting stuck does not mean getting stopped.
This tier combines Tier 2 concepts and Tier 3 labs, then adds two weeks of real-world projects you can put in a portfolio right away. You will build an Expense Tracker application as the core project, with an optional Web Scraper project for extra practice and range. Each project guide walks through environment setup, designing a program flow before coding, step-by-step implementation, and best practices for clean, modular code. On submission, you get code quality reviews, feedback on adding features like a GUI, and ideas for scaling the project further. Built for people who want proof of ability, not just knowledge, since a portfolio project carries more weight than a certificate alone in most hiring conversations today.
The Instructor-Led Tier adds live expert sessions over 2 to 3 weeks on top of the full self-guided path, covering advanced Python concepts and detailed project reviews with optimization feedback from a real instructor. You also get access to a private community Slack or Discord for ongoing Q&A, project support, and networking with other learners past the course itself. Completing all modules, labs, and projects earns the Python Programming Practitioner certificate, signaling real, validated ability to write clean, efficient Python for production-style work. This is the top tier for anyone who wants direct mentorship and accountability rather than working through material alone, with a credential reflecting completed, reviewed work.
This course covers building a data integration platform that connects enterprise systems like ERP, CRM, and SCM with external sources such as web services and APIs, using no-code AI tools on Azure. You will use LLMs to standardize ingested data, then run queries across the combined dataset to generate insights, reports, and visualizations your team can use directly. The path starts with no-code AI and Azure fundamentals, builds through generative model construction and advanced no-code techniques, and ends with deployment. Built for professionals in manufacturing, retail, and technology who need integrated data pipelines without deep coding expertise. A practical option for teams that want AI-driven analytics fast, using tools that do not require a dedicated engineering build.
This course teaches you to build a system that uses LLMs to pull structured data out of documents like invoices, contracts, reports, and forms automatically. You will learn to validate and transform the extracted data, then feed it into enterprise systems such as ERP, CRM, or databases, plus connect to external sources to verify and enrich what you extract along the way. The path starts with no-code AI and Azure basics, then builds through generative model construction into deployment. Aimed at people in finance, healthcare, legal, and logistics who want to automate document work that is currently slow, manual, and error-prone. This is one of the more directly applicable paths for cutting real operational cost in document-heavy teams.
This course covers building a platform that customizes training programs for employees based on their role, performance data, and career goals. You will use LLMs to generate personalized learning materials, track individual progress, and tailor development plans instead of relying on one-size-fits-all training content for everyone. The path moves from generative AI foundations through advanced techniques into a real-world application you can point to. Built for HR professionals, L&D teams, and educators who want to apply AI to employee development rather than just read about it. Corporate HR departments and training firms are actively hiring for these skills, since personalized, data-driven training is becoming the expectation for how companies grow and retain talent.
This course walks through building an AI travel planning tool that generates personalized itineraries based on a user’s budget, preferences, and travel history. You will integrate live data sources including flight schedules, hotel availability, local attractions, and weather forecasts so recommendations update as circumstances change. The build covers automated booking flows, travel advisories, and dynamic itinerary adjustments, all powered by LLMs working across multiple data feeds at once. Content progresses from generative AI foundations through advanced techniques into a real-world application you complete yourself. Suited for anyone who wants to design AI products for the travel and hospitality industry, where personalization at scale is becoming the standard customers expect rather than a nice extra.
The Learning Path program equips students from diverse life experiences and educational backgrounds with essential AI skills, enabling them to become citizens of today’s AI-centric world.
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