My Learning Roadmap
This Learning Roadmap is like a guidebook, based on courses I’ve taken and ones I’m planning to take. It’s mostly about computer science, but with a strong focus on machine learning and artificial intelligence.
The roadmap covers many topics including machine learning, deep learning, natural language processing, and algorithms and data structures. It also covers aspects of project management, entrepreneurship and teaching methods.
The roadmap isn’t just an educational resource; it’s also a reflection of my own curiosity. There are some essential fields to work life like management and agile methodologies. I thing that by following it, one could potentially expand their skill set and boost their job prospects.
Each part tells you how long it may take and gives you links to the courses.
I’m definetly not planning to take all the courses. They are not at all a prerequisite to get in the field data science or computer science, sometimes you just need to take two or three courses of each part. Maybe I will talk about this later in separate posts. Besides, as I embark on a course, I may decide to alter its path or even remove it from the selection 🛠.
The content of this roadmap is definitely subject to continuous review and updates 💡.
Data Science & Machine Learning
- Machine Learning Specialization | Coursera (4 months, 9h/week) by Stanford, DeepLearning.AI
- Deep Learning Specialization | Coursera (5 months, 9h/week) by DeepLearning.AI
- Natural Language Processing Specialization | Coursera (4 months, 6h/week) by DeepLearning.AI
- Practical Deep Learning for Coders | fast.ai (7 weeks, 10h/week) by Jeremy Howard
- Machine Learning Engineering for Production (MLOps) Specialization | Coursera (4 months, 5h/week) by DeepLearning.AI
- Data Science: Statistics and Machine Learning Specialization | Coursera (5 months) by Johns Hopkins University
- Mathematics for Machine Learning Specialization | Coursera (4 months, 4hours/week) by Imperial College London
- fast.ai Code-First Intro to Natural Language Processing - YouTube by Rachel Thomas
- fast.ai Introduction to Machine Learning for Coders - YouTube by Jeremy Howard
- Neural Networks: Zero to Hero - YouTube by Andrej Karpathy
- Computational Linear Algebra 1: Matrix Math, Accuracy, Memory, Speed, & Parallelization - YouTube by Rachel Thomas
- CMU Advanced NLP 2022: Introduction to NLP - YouTube by Graham Neubig
- Introduction to Deep Learning: – 170 Video Lectures from Adaptive Linear Neurons to Zero-shot Classification with Transformers by Sebastian Raschka
- Introduction to Machine Learning– 90 Video Lectures about Python Basics, Tree-based Methods, Model Evaluation, and Feature Selection by Sebastian Raschka
- AI For Everyone | Coursera (4 weeks)
- Methods and Statistics in Social Sciences | Coursera (8 months)
- Artificial Intelligence: an Overview | Coursera (4 months)
Algorithms & Data Structures
- Algorithms | Coursera (4 months)
- Data Structures and Algorithms | Coursera (6 months)
- Analysis of Algorithms | Coursera (12 weeks)
- Coding Interview Preparation | Coursera | Meta
- Algorithms, Part I | Coursera (6 weeks)
- Algorithms, Part II | Coursera (6 weeks)
- Algorithmic concepts | Super Study Guide
- Algorithms and Data Structures MicroMasters® Program | edX (1 year, 4 months)
- Data Structures and Algorithms Professional Certificate | edX (5 months)
- Algorithm Design and Analysis | Stanford Online (Self-Paced)
- Introduction to Algorithms | MIT OpenCourseWare (Free Course)
- Algorithms and data structures: superstudy guide
- Meta Database Engineer Professional Certificate
Computer Science & Engineering
- Computer Science: Algorithms, Theory, and Machines | Coursera (11 weeks)
- Introduction to Computer Information Systems | Coursera (8 months)
- Computer Architecture | Coursera (11 weeks)
- Computer Communications | Coursera (4 months)
- Circuits and Electronics XSeries Program | edX (9 months)
- Introduction to Computer Science and Programming Using Python | edX (9 weeks)
- Game Theory | Coursera (7 weeks)
Business & Management
- Culture-Driven Team Building Specialization | Coursera (4 weeks)
- DevOps, Cloud, and Agile Foundations | Coursera (5 months)
- Google Project Management: Professional Certificate | Coursera (6 months)
- Agile Leadership | Coursera (5 months)
- Project Management Principles and Practices | Coursera (4 months)
- Management Consulting | Coursera (5 months)
- Entrepreneurship | Coursera (6 months)
Education & Learning
- Learning How to Learn: Powerful mental tools to help you master tough subjects | Coursera (3 weeks)
- Uncommon Sense Teaching Specialization | Coursera (3 months)
- New Learning: Principles and Patterns of Pedagogy | Coursera (6 weeks)
- Learning, Knowledge, and Human Development | Coursera (6 weeks)
- Advanced Interviewing Techniques | Coursera (21 hours)
Misc
Machine learning libraries
Resources
- Github: Overview of Modern Deep Learning Techniques Applied to Natural Language Processing
- Github: Natural Language Processing with Transformers
- Github: teaching nlp
- Github: NLP Essentials
- Transformers from Scratch
- Machine learning roadmap 2020
- INFO8010 Deep Learning, ULiège Spring 2021
- AI Expert Roadmap
- Tech Interview Handbook
- Coding Interview University