Doing courses
Posted on Jan 30, 2019
To become an expert in AI field, should learnt and know some of below important courses.
I. Programmimg 
1. Python
- Basic
- Python from sololearn
- Learnpython.org
- Datacamp.com
- Introduction to Python for Data Science (Free Course)
- Python tutorials on Youtube by Corey Schafer
- Python Full course on Youtube by Simplilearn
- Intermediate
- Python Object Oriented Programming on Youtube by Corey Schafer (free)
- Python Beyond Basics – Object Oriented Programming on Udemy (paid course)
- Python for Everybody Specialization by University of Michigan
- Python blog - The Web Dev
- Programming for Everybody (Getting Started with Python)
- Python Data Structures
- Using Python to Access Web Data
- Using Databases with Python
- Capstone: Retrieving, Processing, and Visualizing Data with Python
- Read books and practice Coding
2. C++ 
- Start
- C++ Programming All-in-One Tutorial Series (10 HOURS!) by Caleb Curry
- C++ Tutorial on Youtube by Derek Banas
- Let’s Learn C++ on Youtube by Trevor Payne
- Basic
- C++ Tutorial for Complete Beginners Course (free course from Udemy)
- C++ from sololearn
- C++ for Programmer Course (free course from Udacity)
- Advanced
- Learn Advanced C++ Programming Course (paid course from Udemy by John Purcell)
- Youtube
- Read books and practice
Practice
- LeetCode: Top Interview Questions
-
3. Matlab
- Machine Learning Onramp (free course)
II.1. Machine Learning
- Basic
- Machine Learning Course by Andrew Ng - offered by Stanford - ref or Chinese ref
- Machine Learning Full Course from Youtube Simplilearn
- Advanced
- Read books
- Mathematics for Machine Learning by Marc Peter Deisenroth, A. Aldo Faisal, Cheng Soon Ong
II.2. Deep Learning
-
Course
- Intro to TensorFlow for Deep Learning Course by Udacity - Read Jessica Yung’s Blog
- Course1: Neural Networks and Deep Learning in Deep Learning Specializaton by Coursera - Doing
- Reference for the Courses
-
Reading
- Neural Networks and Deep Learning by Michael Nielsen
III. Algorithm 
- Coursera-Algorithm part1 by Princeton University
-
Algorithm Specialization by Dr. Tim RoughGarden – Stanford (free to watch videos but pay to do assignment).
- Course 1: Divide and Conquer, Sorting and Searching, and Randomized Algorithms
- Course 2: Graph Search, Shortest Paths, and Data Structures from UNIVERSITY OF CALIFORNIA SAN DIEGO
- Course 3: Greedy Algorithms, Minimum Spanning Trees, and Dynamic Programming
- Course 4: Shortest Paths Revisited, NP-Complete Problems and What To Do About Them
- Data Structures and Algorithms Specialization
- Lectures of 2 classes are also available on Youtube Algorithm lectures
- Discrete math by TheTrevTutor on Youtube
- Graph Theory by Sarada Herke on Youtube
- Algorithms and Data Structures by Ravindrabadu Ravula on Youtube
- Cisco Networking Basics Specialization on Coursera
- Introduction to Operating Systems on Udacity (free materials and taught by GATech professor)
- Intro to Computer Science & Programming by MIT on Youtube
IV. Robotics
- Robotics: Computational Motion Planning in Coursera by University of Pennsylvania
-
Perception
- Week1.
- Week2 3 4
- Reference for the Courses
-
Notes: How to run file.p
- Run » cd ‘C:\Disk\folder\submit.p’ in Command Window in Matlab
- Run » dir - to see all the file
- Run » submit then Enter ( do not run » submit.p)
- Robotic with Python
V. Software
- ROS
- Basic
- Advance
Blogs
- AI-ML-DL
-
ML road - Ong Xuan Hong
- Giải tích (Analytics)
- tìm độ lỗi cực tiểu cho mô hình, cực đại hóa khả năng - Đại số tuyến tính (Linear algebra)
- nhân ma trận trong xử lý ảnh, biểu diễn và thao tác sử dụng bảng - Toán rời rạc (Discrete mathematics)
- hỗ trợ phép đếm trong xác suất - Lý thuyết đồ thị (Graph theory)
- phân tích mạng xã hội - Xác suất thống kê (Statistics and probability)
- xây dựng mô hình dự đoán dựa vào dữ liệu quá khứ "educated gues"
- Giải tích (Analytics)
- Machine Learning Mastery
Webdevelopments
- https://www.youtube.com/channel/UC1ofxnYkvcTI79_ycsZ4Zgg
