Learn the foundations of generative AI and large language models (LLMs)

Generative AI is transforming how organisations create, analyse, and work with information. On this three-week course, you’ll explore the technology behind modern generative AI and develop practical skills for working with large language models (LLMs).

You’ll discover how generative AI differs from traditional machine learning, explore the transformer architecture behind today’s LLMs, and learn how models such as GPT are trained. You’ll also compare proprietary and open-source LLMs while considering important responsible AI issues, including bias, safety, and misuse.

Develop practical prompt engineering skills

Effective prompts are essential for getting reliable results from generative AI. You’ll learn how to structure and refine prompts, applying zero-shot, one-shot, and few-shot prompting techniques to tasks.

Through iterative testing and debugging, you’ll develop the ability to identify weak prompts and improve their performance. You’ll then explore advanced prompt engineering techniques, including chain-of-thought, tree-of-thought, self-consistency, and generated-knowledge prompting.

Apply generative AI responsibly and securely

As generative AI becomes increasingly important in the workplace, understanding its risks is just as important as knowing how to use it. You’ll explore adversarial prompting and prompt injection, learning how these techniques can compromise LLM applications and how to defend against them.

You’ll also discover how human-in-the-loop refinement can improve AI outputs, helping you develop a more reliable and responsible approach to working with generative AI.

By the end of the course, you’ll understand how LLMs work and have the prompt engineering expertise to apply generative AI effectively.

Syllabus

Week 1
Generative AI and LLM Fundamentals
- Welcome to Generative AI: Understanding the Landscape
  In this Edureka course, explore what Generative AI is, how it differs from traditional AI, and the key technologies, models, and applications shaping today’s evolving AI landscape.
- Inside the Transformer Architecture
  Explore how Transformers power modern LLMs, from tokenisation and embeddings to attention and training, and understand how these components work together to process and generate language.
- Exploring the LLM Landscape and Responsible AI
  Explore the evolving LLM landscape, compare key model types and capabilities, and understand the principles of responsible AI, including fairness, transparency, safety, privacy, and ethical use.
Week 2
Prompt Engineering Essentials
- Anatomy of an Effective Prompt: From Intent to Output
  This is more engaging and clearly reflects the key elements of prompt design—intent, context, instructions, constraints, and desired output.
- Prompting Strategies: Zero-Shot, One-Shot, and Few-Shot
  This Edureka activity introduces three core prompting strategies and shows how they can be applied to improve LLM responses.
- Task-Specific Prompting and Debugging
  This better reflects the practical workflow of creating prompts for specific tasks, evaluating their outputs, and systematically improving weak prompts.
Week 3
Advanced Prompting Strategies
- Reasoning Prompts: Guiding LLMs Through Complex Tasks
  This is stronger than simply “Reasoning Prompts” because it clearly communicates the purpose and practical value of the technique.
- Structured and Compositional Prompting: Building Complex Prompts
  This is clearer and more engaging, while highlighting how structured instructions and prompt components can be combined to handle complex tasks effectively.
- Adversarial Prompting and Human-in-the-Loop: Testing and Improving AI Safety
  This title clearly connects adversarial prompting with human oversight, while emphasising the practical goal of making AI systems safer and more reliable.
- Context Engineering: Beyond the Prompt
  This is concise, professional, and aligns well with the curriculum by positioning context engineering as the next step beyond traditional prompt engineering.

Prove you're job ready

Highlight the new, job-relevant skills you’ve gained and supplement existing qualifications with a hard-earned, industry-specific digital certificate – plus one for every course within your ExpertTrack.

Learn the latest in your chosen industry or subject.
Complete each course and pass assessments.
Receive certificates validated by the educating organisation.
Impress employers with learning outcomes you can add to your CV.
Make your career dreams a reality.

Download a PDF

Learning on this course

On every step of the course you can meet other learners, share your ideas and join in with active discussions in the comments.

What will you achieve?

By the end of the course, you‘ll be able to...

Explain the fundamentals of generative AI, large language models, transformers, tokenisation, attention, and the LLM training lifecycle.
Compare proprietary and open-source LLMs based on their capabilities, use cases, and responsible AI considerations.
Apply zero-shot, one-shot, and few-shot prompting to question answering, summarisation, classification, and other language tasks.
Evaluate prompt injection risks and apply defensive and human-in-the-loop techniques to improve LLM safety.
Develop an end-to-end prompted application that combines effective prompting, reasoning, safety, and context-management techniques.
Design context-engineering workflows using retrieved knowledge, conversation memory, context ordering, and token-budget management.

Who is the course for?

This introductory course is designed for software developers, data analysts, machine learning practitioners, and technical professionals who can already program in Python and understand basic machine learning concepts, and who now want to build practical generative AI skills.

No prior experience with large language models or prompt engineering is required. It is ideal for developers moving into AI product work, data professionals adding GenAI capability to their role, and engineers preparing for prompt engineer or junior LLM developer positions. Learners should be comfortable writing Python and reading code before starting. By the end, they will understand how LLMs work and be able to design reliable prompts for real tasks.

Who will you learn with?

Edureka Instructors

Who developed the course?

Edureka

Edureka is a global online learning platform offering industry-focused training in emerging technologies such as Cloud, AI, GenAI, Data Science, DevOps, and Cybersecurity, helping professionals upskill and advance their careers.

About this ExpertTrack

Build job-ready generative AI and LLM expertise, from prompt engineering and application development to RAG and AI systems.

Find out more

Start learning today - free 2-day trial

After your free trial you can:

Pay $39 per month to keep learning online
Have complete control over your subscription; you can cancel any time
Work at your own pace and set your own deadlines at every stage
Only pay while you’re learning; the subscription will cancel automatically when you finish
Complete online assessments to test your knowledge and prove your skills
Earn digital course certificates and a final award that you can share online, with potential employers, and your professional network
Keep access to the content of courses you complete even after your subscription ends

Start your free 2-day trial

Learning on FutureLearn

Your learning, your rules

Courses are split into weeks, activities, and steps to help you keep track of your learning
Learn through a mix of bite-sized videos, long- and short-form articles, audio, and practical activities
Stay motivated by using the Progress page to keep track of your step completion and assessment scores

Join a global classroom

Experience the power of social learning, and get inspired by an international network of learners
Share ideas with your peers and course educators on every step of the course
Join the conversation by reading, @ing, liking, bookmarking, and replying to comments from others

Map your progress

As you work through the course, use notifications and the Progress page to guide your learning
Whenever you’re ready, mark each step as complete, you’re in control
Complete 90% of course steps and all of the assessments to earn your certificate

Want to know more about learning on FutureLearn? Using FutureLearn