Use AI Like a Pro
Published by Pearson
Level up your AI developer skills with LLMs, prompts, APIs, and tools like OpenAI and Claude
- Goes beyond theory with live coding, real-world APIs (OpenAI, Claude, Ollama), and project-based demos using Python/Node.js.
- Builds up to advanced concepts like multimodal LLMs, agents, and Retrieval-Augmented Generation (RAG), often skipped in beginner workshops.
- Teaches practical techniques for reducing API usage costs, structuring prompts for reliability, and selecting the right open-source tools.
This live training is a fast-paced, hands-on introduction to the world of large language models (LLMs) and modern AI applications. Designed for developers, product teams, and tech-savvy professionals, it blends foundational AI theory with practical skills in prompt engineering, API usage, and advanced capabilities like agents and multimodal models. Participants will learn how LLMs actually work, how to interact with them effectively through prompts, and how to build intelligent applications using cutting-edge tools like OpenAI, Claude, Hugging Face, and more.
As AI rapidly becomes embedded in every aspect of software development and business operations, understanding how to work with LLMs isn’t just valuable—it’s essential. This class empowers attendees to go beyond passive use of AI tools, giving them the knowledge to build, optimize, and deploy AI-driven features responsibly and cost effectively. Whether you're prototyping a chatbot, integrating smart suggestions into a product, or exploring research workflows, this workshop equips you with the technical fluency to lead in the AI-powered future.
What you’ll learn and how you can apply it
- Build AI-powered apps responsibly, with awareness of ethical risks like hallucinations and prompt injection.
- Design and optimize prompts to guide LLMs toward accurate, structured, and cost-efficient outputs.
- Integrate LLM APIs into real-world projects using tools like OpenAI, Claude, and open-source models from Hugging Face.
- Leverage advanced AI capabilities such as agent workflows, Retrieval-Augmented Generation (RAG), and multimodal inputs.
- Learn how to craft smarter prompts and understand API usage.
This live event is for you because...
- You’re a developer, data scientist, or product manager who wants to work hands-on with real AI tools.
- You want to understand how LLMs work, including tokens, temperature, and prompting.
- You’re ready to build real applications using APIs like OpenAI, Claude, or Hugging Face.
- You’re a beginner or intermediate learner who wants practical, responsible AI skills you can use right away.
Prerequisites
- No prior AI or machine learning experience is required — curiosity and a willingness to learn are most important.
- Basic programming knowledge in Python or JavaScript (enough to read and write simple scripts).
- Familiarity with using APIs or developer tools (e.g., Postman, REST calls, or browser-based playgrounds).
Course Set-up
- Any terminal. I recommend Iterm (https://iterm2.com/downloads.html)
- Jupyter notebook (optional) https://jupyter.org/install
- Install python https://github.com/aashimaahuja/ai_workshop/blob/main/segment3/python_installation.md
Recommended Preparation
- Attend: How to Prompt Like a Pro by Tim Warner
Recommended Follow-up
- Watch: Generative AI Toolbox by Shaun Wassell
Schedule
The time frames are only estimates and may vary according to how the class is progressing.
Cracking the Code — The Theory Behind AI & LLMs (45 minutes)
- What is an LLM?
- How LLMs Work (tokens, self-supervised learning)
- Determinism vs Non-Determinism (temperature, randomness)
- Token-based pricing (input vs output tokens)
- Compute considerations: Model size vs data size
- Common pitfalls: Hallucinations, reproducibility
Break (5 minutes)
Prompt Like a Pro — Crafting Smarter Interactions (45 minutes)
- Prompt engineering principles
- In-context learning, zero-shot, few-shot, and chain-of-thought prompting
- Prompting tricks (temperature, max tokens, structuring)
- Generating structured outputs (JSON, tables, markdown)
- Hands-on with ChatGPT, Claude, or other LLM APIs
Break (10 minutes)
Building with Brains — APIs, Inference, and Cost Tricks (45 minutes)
- Accessing LLMs via APIs (Python/Node.js demos)
- Parameters overview (temperature, max_tokens, top_p)
- Batching for cost optimization
- Overview of aggregators and open-weight models (Hugging Face, Ollama)
- Hands-on code demo: Send your first batched request
Break (10 minutes)
Beyond Text — Exploring Modalities and Agents (40 minutes)
- Multimodal models (Vision/Audio inputs & outputs)
- Reasoning and CoT in advanced models (Gemini Flash, DeepSeekR1)
- Agents: What they are and how they work (Operator, AutoGPT, Deep Research)
- Overview of RAG, CAG, and VectorDB integration
- Demos using tools like Cursor AI, Perplexity AI, and NotebookLM
Break (5 minutes)
Keep it Safe — Ethics, Hallucinations & Guardrails (25 minutes)
- Prompt Injection and Jailbreaks
- Avoiding hallucinations
- Reproducibility and auditability in LLM output
- Final tools & best practices roundup
- Demos using tools like Cursor AI, Perplexity AI, and NotebookLM
Course wrap-up (10 minutes)
- Summary
- Q&A
- Share Prompt Cheat Sheets & Toolkits
Your Instructor
Aashima Ahuja
Aashima Ahuja is a front-end engineer and a content creator. She has a passion for teaching front end. She has taken several trainings all over the world and is an active conference speaker. She has a bachelor's degree in Computer Science and has experience working in Big Tech companies.