Here are the best ones you shouldn’t skip in 2026:
Generative AI Explained
Get a clear view of what generative AI is and why it matters in real work.
What you’ll learn:
→ The core idea behind generative AI
→ Where it’s used in real products and teams
→ Common limits, risks, and where it’s heading next
Learn how AI jobs actually run inside modern data centers.
What you’ll learn:
→ The basics of AI, ML, and deep learning in infrastructure terms
→ How training differs from inference in practice
→ When GPUs win, when CPUs are enough, and why
Accelerate Data Science Workflows with Zero Code Changes
Make data pipelines faster by using GPUs, without rewriting your codebase.
What you’ll learn:
→ How CPU and GPU workflows can work together
→ Ways to speed up data processing with GPU acceleration
→ How to reduce training time without changing your code
Build and run AI on edge hardware, not just in the cloud.
What you’ll learn:
→ How to collect and label data for your project
→ How to train a neural network for a real use case
→ How to run inference with your own custom model
Improve LLM answers by letting the model pull in outside knowledge.
What you’ll learn:
→ The basics of Retrieval-Augmented Generation
→ Practical GenAI methods beyond simple prompting
→ How embeddings and vector databases fit into RAG
Go beyond chatbots. Build agents that can run tasks using LLMs.
What you’ll learn:
→ How to set up an environment for LLM agents
→ How agent inference connects to tools and interfaces
→ How microservices can power scalable AI agents
Create real-time video analytics on Jetson devices.
What you’ll learn:
→ How DeepStream pipelines are built and deployed
→ How to process multiple video streams at once
→ How to connect inputs and outputs in a real system
A quick, hands-on way to understand how neural nets learn, inspired by biology.
What you’ll learn:
→ The basic mechanics of neural network learning
→ How neuron-style models are trained
→ Practical TensorFlow 2 exercises you can follow along with
Each one is a hands on notebook with short theory, code, and exercises
You practice directly with Claude, then tweak prompts in a playground
Beginner level - make your prompts stop sucking
Chapter 1: Basic prompt structure
- State the goal
- Specify audience and format
- Add constraints and examples
You stop saying “write about X” and start giving tight instructions.