AI Learning Series:Level Up Your Skills with courses, regardless of your tech background, from Google, Microsoft, Coursera, Kaggle and Github
Great courses for beginners(non-tech) and developers. Beginner courses highly encouraged for people with no tech background.
Want to understand and navigate the world of AI?
I have completed most of these courses and gone through course content of every course and found them very helpful. These are also good for beginners.
These courses give you the easy learning path, no matter your background or goals.
I have categorized these for everyone who might read my newsletter.
Curious Case of AI: Non-Technical Learners and for anyone
Goal: Understand the basics of AI, and discover free AI tools to help with your daily life.
AI for Everyone by Andrew Ng (Coursera) - https://www.coursera.org/learn/ai-for-everyone
Duration: Roughly 6 hours.
Google AI Essentials (Google) -
https://www.coursera.org/google-learn/ai-essentials/
Duration: Roughly 8-10 hours.
Curious case of AI: Technical Learners
Goal: Get started with coding and machine learning skills in AI
AI for Beginners GitHub Curriculum (GitHub) - https://github.com/microsoft/AI-For-Beginners
Duration: 12 weeks (flexible, self-paced).
Whats Covered : You can review the mindmap of the course.
Machine Learning Crash Course (Google) - https://developers.google.com/machine-learning/crash-course
Duration: Around 15 hours.
Whats Covered : There are 4 major modules which covers submodules.
ML Models: These modules cover the fundamentals of building regression and classification models.
Data: These modules cover fundamental techniques and best practices for working with machine learning data.
Advanced ML models: These modules cover advanced ML model architectures.
Real-world ML: These modules cover critical considerations when building and deploying ML models in the real world, including productionization best practices, automation, and responsible engineering.
5-Day Gen AI Intensive Course with Google Learn Guide(Kaggle)
https://www.kaggle.com/learn-guide/5-day-genai
Whats Covered:
Day 1: Foundational Models & Prompt Engineering - Explore the evolution of LLMs, from transformers to techniques like fine-tuning and inference acceleration. Get trained with the art of prompt engineering for optimal LLM interaction.
Day 2: Embeddings and Vector Stores/Databases - Learn about the conceptual underpinning of embeddings and vector databases, including embedding methods, vector search algorithms, and real-world applications with LLMs, as well as their tradeoffs.
Day 3: Generative AI Agents - Learn to build sophisticated AI agents by understanding their core components and the iterative development process.
Day 4: Domain-Specific LLMs - Delve into the creation and application of specialized LLMs like SecLM and Med-PaLM, with insights from the researchers who built them.
Day 5: MLOps for Generative AI - Discover how to adapt MLOps practices for Generative AI and leverage Vertex AI's tools for foundation models and generative AI applications.