AI & machine learning
My Learning Roadmap
Your personalized learning journey
Phase 1: The Foundational Learner
Weeks 1-8
Master the basics of Python for data science and understand core machine learning concepts like supervised and unsupervised learning.
Phase 2: The Practical Developer
Months 3-6
Build and train your first models using frameworks like Scikit-learn and TensorFlow. Begin exploring prompt engineering with LLMs.
Phase 3: The Advanced Engineer
Months 6-12
Dive into deep learning, fine-tune pre-trained models from Hugging Face, and master complex algorithm design for specialized tasks.
Endgame: The AI Strategist & Innovator
Year 1+
Lead AI projects, architect novel solutions, and contribute to the field through research or building specialized AI-powered products. Your expertise now drives significant business or scientific innovation.
TensorFlow Developer Professional Certificate
Learn to build and train powerful neural networks using TensorFlow and gain practical skills to develop models for computer vision, NLP, and time series data.
Clinical Data Analysis using Python (Pandas & SciPy)
Utilize core Python libraries to clean, process, and analyze complex clinical trial datasets and patient cohorts effectively.
Foundational Python for Data Scientists
Master the essential libraries (Pandas, NumPy) and scripting structures required for professional data manipulation and efficient cleaning.
Scikit-learn Official Documentation & Tutorials
The official guide to one of Python's most popular ML libraries, providing detailed explanations and code examples for a vast array of algorithms.
Intro to Machine Learning
Get started with machine learning using Pandas and Scikit-learn to build your first models and learn core concepts like model validation.
Practical Deep Learning for Coders
Take a hands-on, code-first approach to building and training world-class models for computer vision and NLP using the fastai library and PyTorch.
Introduction to Prompt Engineering
Learn fundamental and advanced techniques for crafting effective prompts to get superior results from large language models in this comprehensive open-source course.
Deep Learning Specialization
Master the foundations of deep learning and learn how to build and train neural networks for cutting-edge projects in computer vision, NLP, and more.
The Hugging Face Course
Gain hands-on experience using the Hugging Face ecosystem to fine-tune and deploy state-of-the-art language models for natural language processing.
Machine Learning Specialization
Learn the core theory behind machine learning algorithms and how to implement them in Python in this comprehensive specialization from a Stanford expert.