Turing College

Course Description:

Master the skills to design and deploy production-ready AI applications powered by large language models. This AI Engineering course is built for developers who want to apply AI in real systems, not just experiment with it. You’ll work with Python or JavaScript, LangChain, and leading model APIs to build applications that automate workflows, interact with users, and connect to real-world data.

The program focuses on three key areas: building a strong foundation in LLM application development, creating interactive applications that integrate external data using retrieval-augmented generation (RAG) and vector databases, and designing AI agents capable of handling complex, multi-step tasks. Through hands-on projects, you’ll gain practical experience building structured outputs, prototyping chatbots, and deploying intelligent systems tailored to real engineering challenges.

By the end of the course, you’ll gain the practical skills needed to work with LLMs in production, qualify for AI engineering roles, and apply AI to automate and enhance modern software systems.

Course Description:

Curious about the ethical risks of AI and what to actually do about them? If you’re building or working with machine learning models, but lack clear methods to detect bias or evaluate fairness, this AI Ethics program is for you.

You’ll learn how to apply fairness metrics such as demographic parity and equalized odds, and implement mitigation techniques at the data, model, and prediction levels. You’ll build fairness assessment pipelines in Python, evaluate models built with libraries like scikit-learn, and apply fairness intervention frameworks across the ML lifecycle. The program also covers fairness challenges specific to large language models and AI systems.

Through hands-on exercises and a practical specialization, you’ll audit real models, apply bias mitigation techniques, and implement monitoring strategies. By the end of the program, you’ll be able to identify fairness risks, improve model outcomes, and integrate fairness practices into production machine learning workflows.

Course Description:

Use AI to work faster, make better decisions, and stay competitive in your career. This AI for Business course is built for business professionals, analysts, marketers, managers, and other non-technical roles who want to automate tasks, analyze data, and improve their daily workflows independently, without relying on engineers or tech teams.

The program is structured in two main modules. First, you’ll build AI literacy - you’ll learn how tools like ChatGPT, Copilot, and Gemini work, how to write effective prompts, and how to use AI safely and reliably in real business scenarios. Then, you’ll focus on practical applications - you’ll learn how to analyze data using AI with Google Sheets, SQL, and Python, automate workflows with tools like Zapier or n8n, and use AI to streamline reporting, research, and communication.

Through hands-on exercises and real business use cases, you’ll build skills you can apply immediately in your role. By the end of the program, you’ll be able to automate repetitive work, extract insights from data faster, and confidently use AI to improve productivity and decision-making in your organization.

Course Description:

You’ve tried using AI tools like ChatGPT, but the results are inconsistent. Sometimes they save time, other times they create more work. It’s unclear which tools to use or how to apply them effectively. This AI Literacy course gives you a clear, practical foundation to understand how AI works and use it confidently in your daily tasks.

The program covers the fundamentals of AI and how to apply it in real situations. You’ll learn how to write effective prompts, use tools like ChatGPT, Gemini, and Claude, and automate repetitive tasks in emails, spreadsheets, and meetings. You’ll also learn how to generate content, analyze information faster, and understand the limitations, risks, and best practices of using AI responsibly.

Through hands-on exercises and a capstone project, you’ll apply your skills to a real use case. By the end of the course, you’ll understand what AI can and can’t do, choose the right tools for different situations, and use AI effectively and responsibly as part of your daily work.

Course Description:

Turn data into insights that drive real business decisions. This Data Analytics program is designed for beginners and career switchers who want to become data analysts and work with the tools companies use to understand performance, customers, and growth. You’ll learn how to collect, analyze, and visualize data to answer business questions and support decision-making.

The program is structured across four core modules covering the full analytics workflow. You’ll start with spreadsheets and SQL to extract and prepare data, then learn to create dashboards using Tableau or Power BI to communicate insights clearly. You’ll apply key analysis techniques such as cohort analysis, funnel analysis, segmentation, and A/B testing, and use Python to analyze larger datasets and automate analysis.

Through 17 hands-on projects and a capstone, you’ll build a portfolio that proves your skills. You can also specialize in areas like product or marketing analytics.

By the end of the program, you’ll be able to analyze data independently, present insights to stakeholders, and qualify for roles such as data analyst, product analyst, or marketing analyst.

Subjects:
Database Management, A/B Testing, Python, Data Analytics, SQL, Data Visualization

Course Description:

Turn data into real insights and build machine learning models that solve business problems. This Data Science & AI program is designed for those who want to become data scientists. You’ll learn how to analyze data, build predictive models, and turn complex datasets into clear, actionable insights.

The program is structured across three core modules. First, you’ll build strong programming and data analysis foundations using Python, Pandas, and SQL to clean, explore, and visualize data. Then, you’ll learn statistical inference, including hypothesis testing, regression, and causal analysis, to answer real-world questions with confidence. Finally, you’ll master machine learning, training and deploying models using tools like Scikit-Learn, XGBoost, and PyTorch to solve problems such as prediction, classification, and forecasting.

Through 15 hands-on projects and a capstone project, you’ll build a portfolio that proves your skills. You can also specialize in Natural Language Processing or Computer Vision to deepen your AI expertise.

By the end of the program, you’ll be able to design end-to-end data science solutions and qualify for roles such as data scientist, machine learning engineer, or AI specialist.

Subjects:
Python, Machine Learning, Data Analytics, SQL, Data Visualization, Data Science

Course Description:

Search is changing - instead of showing only links, tools like ChatGPT and Google’s AI Overviews generate answers directly, often without users visiting your website. This Generative Engine Optimization course is built for SEO specialists, content marketers, and growth professionals who want to understand how generative search works and ensure their content stays visible, cited, and discoverable in AI-generated results.

The program is structured across four focused sprints covering both strategy and implementation. You’ll learn how generative engines retrieve and cite content, how to measure AI visibility using tools like Semrush, and how to design content and technical structures that increase your chances of being referenced in AI answers. You’ll also learn how to run structured experiments and build a repeatable GEO strategy that complements your existing SEO efforts.

Through experiments and a hands-on capstone project, you’ll apply GEO methods to a real website. By the end of the course, you’ll be able to audit AI visibility for your business, implement GEO optimizations, and build a practical operating system to keep your content visible and competitive in AI-driven search.

Course Description:

Launch your tech career with AI in your toolbox. This Software & AI Engineering program is built for beginners who want to become developers and build real software and AI-powered applications from scratch.

The program is structured in two main modules. First, you’ll build a strong software engineering foundation - you’ll learn Python, object-oriented programming, Git, and how to work with APIs and real-world data. Then, you’ll move into AI engineering, where you’ll learn prompt engineering, retrieval-augmented generation (RAG), and how to build intelligent applications and AI agents that automate tasks and interact with users.

Through hands-on projects and a capstone, you’ll build a portfolio that proves your skills. By the end of the program, you’ll be able to design, build, and deploy real software and AI applications, qualify for junior developer or AI engineering roles, and continue growing as a software engineer.