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AI IS DISRUPTING EVERY INDUSTRY

Healthcare83%
Retail77%
Media & Entertainment73%
Financial Services80%

Top AI Updates:

ACP Explained: The Vendor-Neutral Backbone for Cooperative AIGood Vibes: How to Use AI to Talk to Your CodebaseIs Google's A2A Protocol the cure for disjointed AI agents?Does Modern AI Truly Think?Is BAGEL The Future of Multimodal Understanding and Generation?Google I/O 2025: A Generative AI Playground for DevelopersHow Microsoft's WHAMM Uses AI to Render Gameplay in Real Time

The AI future is here.
Are you ready to build it?

Ready to build
the AI future?

Get hands-on with the Generative AI
skills you need to stay ahead.

Get hands-on with the Generative AI skills you need to stay ahead.

Begin Your 21-Day Free Learning Journey

AI IS DISRUPTING EVERY INDUSTRY

Healthcare83%
Retail77%
Media & Entertainment73%
Financial Services80%

Top AI Updates:

ACP Explained: The Vendor-Neutral Backbone for Cooperative AIGood Vibes: How to Use AI to Talk to Your CodebaseIs Google's A2A Protocol the cure for disjointed AI agents?Does Modern AI Truly Think?Is BAGEL The Future of Multimodal Understanding and Generation?Google I/O 2025: A Generative AI Playground for DevelopersHow Microsoft's WHAMM Uses AI to Render Gameplay in Real Time

Your Portal to AI Mastery

Your Portal to AI Mastery

Building blocks for effective Generative AI applications.

P
Prompt Engineering
O
Orchestration Frameworks
R
Retrieval Augmented Generation
T
Tuning
A
Agents
L
LLMs

Prompt Engineering

Stop getting generic results. Prompt Engineering is the art of giving AI perfect instructions. Learn to craft commands that unlock powerful, precise outputs every time. Our course transforms you from a basic user into a confident AI director.

Prompt Engineering

Stop getting generic results. Prompt Engineering is the art of giving AI perfect instructions. Learn to craft commands that unlock powerful, precise outputs every time. Our course transforms you from a basic user into a confident AI director.

Orchestration Frameworks

Ready to build real AI applications? Langchain is the framework for connecting LLMs to data, APIs, and tools. Move beyond simple prompts to architect complex, multi-step AI systems. Our course provides the blueprint to become a true AI builder.

Retrieval Augmented Generation

LLMs don't know your private data. Retrieval Augmented Generation (RAG) fixes that. Ground your AI in specific information to get verifiable, trustworthy answers and eliminate errors. Our course teaches you how to build AI that is not just smart, but accurate.

Tuning

Turn a general LLM into a specialized expert. Fine-tuning with LoRA lets you efficiently train models for specific styles or tasks without the massive cost. Stop using generic AI. Our course teaches you to create your own team of perfectly tailored AI specialists.

Agents

Unleash the power of AI teamwork. Agents are the next frontier, and CrewAI lets you build autonomous crews to tackle complex goals. Design and deploy collaborative agents that can research, write, and execute. Our course teaches you to direct your own digital workforce.

LLMs

To truly master AI, you must understand its engine. This course demystifies Large Language Models (LLMs), from tokens to transformers. This foundational knowledge empowers you to build better systems, debug issues, and create more powerful AI solutions.

Benchmark Your AI Skills here

Curious how your AI knowledge stacks up against the industry? Find out with this quick assessment.

Curious how your AI knowledge stacks up against the
industry? Find out with this quick assessment.

Popular AI Topics

Course

Master GitHub Copilot

Learn GitHub Copilot foundations through hands-on lessons: explore AI-assisted coding, Copilot chat, prompt engineering, code reviews, testing, and debugging to incorporate AI into your workflows.

4h

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Code Smarter with Cursor AI Editor

This course covers how Cursor uses integrated AI tools to help modern developers speed up coding, debugging, and project management.

2h 4m

beginner

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Llama Stack: From Fundamentals to Deployment

This course guides you through Llama Stack and its key components, including agentic workflows, RAG systems, safety mechanisms, monitoring, and deployment.

4h 48m

beginner

Course

Grokking the Generative AI System Design

Explore the design of scalable generative AI systems guided by a structured framework and real-world systems in text, image, audio, and video generation.

4h 48m

intermediate

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Guide to Building Python and LLM-Based Multimodal Chatbots

Explore this AI chatbots course to build Python-based multimodal chatbots with Gradio, Rasa, Gemini, and Whisper v3. Learn LLM-powered techniques, RAG integration, and deploy on Hugging Face.

7h

intermediate

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Fundamentals of Retrieval-Augmented Generation with LangChain

Explore this beginner RAG course to learn the basics of retrieval-augmented generation. For hands-on practice, build RAG pipelines using LangChain and create user-friendly applications with Streamlit.

4h

beginner

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Fundamentals of Retrieval-Augmented Generation with LangChain

In this prompt engineering course, learn what is prompt engineering, how to become a prompt engineer, and master AI prompt design with essential techniques, elements, and real-world role use.

7h

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Essentials of Large Language Models: A Beginner’s Journey

In this LLM course, learn the fundamentals, fine-tuning, and evaluation, and explore its architecture and evolution. Discover GPT-2, compare models, and uncover use cases.

2h

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Master GitHub Copilot
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4 h
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Code Smarter with Cursor AI Editor
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2 h 4 m

Latest Insights

Trending AI News

Is GPT-Image-1.5 competitive with Nano Banana?

OpenAI’s GPT-Image-1.5 marks a deliberate return to image generation, focusing on precision, consistency, and real-world workflows. In this newsletter, we test it hands-on against Gemini Nano Banana using the same prompts to see how each model performs in practice. The result is a practical look at where these image models stand today and how to choose between them.
11 mins read

The rise of AI-made music

AI music generation tools like Suno let creators turn text prompts into original, copyright-safe tracks tailored to specific moods, genres, and use cases. This newsletter explains how these systems work, why licensing is becoming more complex, and where AI-generated music fits into modern creator workflows.
10 mins read

IndQA sets a new bar for cultural understanding in AI

IndQA is OpenAI’s cultural reasoning benchmark for Indian languages. Learn what it measures, how scoring works, what results show, and what builders can do next.
11 mins read

The AI Heavyweights of 2025: Gemini 3.0 vs. GPT-5.1

This newsletter breaks down and compares the two frontier AI models: Google’s Gemini 3.0 (scale-first multimodal reasoning with massive context windows) and OpenAI’s GPT-5.1 (refinement-first speed, reliability, and control). You’ll get clear deep dives on strengths, tradeoffs, and real workflow fit, plus a concise comparison and hands-on coding results to help you choose the right model for the job.
14 mins read

How 'Company Knowledge' solves the internal search problem

ChatGPT’s company knowledge feature creates a single conversational interface for internal documents, messages, and repositories. Instead of searching across tools, teams get grounded, citation-backed answers drawn from their existing systems. This newsletter walks through how the feature works and what it means for day-to-day workflows.
9 mins read

Did DeepSeek-OCR just redefine long-context processing?

This newsletter explores how DeepSeek-OCR rethinks long-context processing by compressing text into compact visual representations, cutting token costs while preserving meaning. It breaks down the architecture, the trade-offs, and the broader implications for the next generation of AI models.
14 mins read

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Frequently Asked Questions

How to learn about generative AI?

Generative AI is like a smart machine learning model. It’s not like a human, though—it doesn’t think or feel. But it’s good at spotting patterns. To build a successful career in Generative AI research, you should learn how to create these generative models from the basics. You should know the concepts and techniques for constructing these models.

How to become a generative AI engineer?

We must master the correct methods to use GenAI tools efficiently. Many Generative AI tools create responses from a natural description, commonly called a prompt. Crafting these prompts is an art form. To fully harness the capabilities of Generative AI, gaining a deep understanding of prompt engineering is essential. To establish a career in Generative AI engineering, consider taking these steps:
  1. Get a Bachelor's degree in Computer Science or a conceptually similar major
  2. Get a post-graduate degree in Artificial Intelligence to specialize in the field
  3. Alternatively, you can get certifications in artificial intelligence and machine learning to enhance your abilities
  4. Get involved in real-world AI projects, get feedback from professionals, and learn how to use these tools efficiently.

Does GenAI require coding?

To start a career as a GenAI engineer, the primary skill you need is proficiency in programming. Mastering programming languages like Python, R, Java, and C++ is vital for the development and implementation of GenAI models.

Can I learn GenAI on my own?

You can learn GenAI on your own by following these steps:
  1. Begin with Python and basic problem-solving skills.
  2. Develop an understanding of object-oriented programming.
  3. Understand data science and statistics.
  4. Start learning the theory behind machine learning and AI.
  5. Immerse yourself in deep learning.
  6. Understand how generative AI models work.
  7. Study autoencoders, generative adversarial networks (GANs), and variational autoencoders (VAEs).
  8. Delve into natural language processing (NLP).
  9. Use online resources and courses.
  10. Engage in hands-on projects and challenges.

What skills are needed for Generative AI?

You can start learning GenAI if you’re familiar with the following:
  • Python programming.
  • Mathematics and statistics.
  • Machine learning and deep learning.
  • Data processing and visualization.
  • Domain knowledge and creativity.
  • Communication and collaboration skills.

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