Artificial Intelligence Beginner to Intermediate
AI for Everyday Problem Solving
Harness LLMs, structured prompting, and workflow automation to 10x your daily productivity.
A little progress goes a long way
Mental Models: How LLMs Actually Process Information
Your first lesson is ready when you are.
Level
Beginner to Intermediate
Time to complete
3h 10m
Lessons
4
Learners
18,400
About this course
A practical path from curious to confident
Demystify generative AI models. Learn the underlying mechanics of Large Language Models, master advanced prompt architectures (Few-Shot, Chain-of-Thought, Meta-Prompting), and construct intelligent automated workflows with APIs.
What you'll learn
- Understand tokenization, context windows, and probabilistic text generation
- Construct robust few-shot and chain-of-thought prompt templates
- Eliminate hallucinations with grounding and verification constraints
- Automate document summarization, data extraction, and content pipelines
- Evaluate safety, privacy, and bias in modern AI systems
The learning path
Course curriculum
4 lessons 3h 10m total
What you'll need
- Basic computer literacy
- No coding background required for prompting modules; basic Python knowledge helpful for API lessons
Learn from experience
Meet your instructor
Dr. Maham Khan
AI Researcher & Applied Systems Architect
Maham holds a PhD in Natural Language Processing and consults with enterprises on safe, practical generative AI adoption. She bridges deep scientific theory with practical everyday engineering.
Frequently asked questions
Do I need an expensive GPU to run these tutorials?
No. All tutorials use web-based playgrounds and lightweight cloud API endpoints that run on any laptop.
Can I use free AI models like Claude or Gemini?
Yes, all prompt architectures taught in this course apply universally to OpenAI, Anthropic Claude, Google Gemini, and open-source models like Llama.