Learning plans By Siraj
READM5
Learn_Computer_Science_in_5_Months
This is the Curriculum for “Learn Computer Science in 5 Months” By Siraj Raval on Youtube
Overview
You can find the video here.
5 Month Curriculum
Week 1-2 (Learn Python)
Week 3-4 (Data Structures)
Week 5-6 (Algorithms)
Week 7 (Databases)
Week 8 (Networking)
Week 9-10 (Web Development)
- https://www.youtube.com/watch?v=1u2qu-EmIRc&list=PLhQjrBD2T382hIW-IsOVuXP1uMzEvmcE5
- https://github.com/melanierichards/just-build-websites
Week 11-12 (Mobile Development)
- https://developer.apple.com/library/content/referencelibrary/GettingStarted/DevelopiOSAppsSwift/
- https://developer.android.com/training/basics/firstapp/index.html
Week 13-14 (Data Science)
Week 15-16 (Computer Vision)
Week 17-18 (Natural Language Processing)
Week 19 (Software Engineering Practices)
Week 20 (Blockchain)
Learn_Machine_Learning_in_3_Months
This is the Curriculum for “Learn Machine Learning in 3 Months” this video by Siraj Raval on Youtube
Month 1
Week 1 Linear Algebra
https://www.youtube.com/watch?v=kjBOesZCoqc&index=1&list=PLZHQObOWTQDPD3MizzM2xVFitgF8hE_ab https://ocw.mit.edu/courses/mathematics/18-06-linear-algebra-spring-2010/ ## Week 2 Calculus https://www.youtube.com/playlist?list=PLZHQObOWTQDMsr9K-rj53DwVRMYO3t5Yr ## Week 3 Probability https://www.edx.org/course/introduction-probability-science-mitx-6-041x-2 ## Week 4 Algorithms https://www.edx.org/course/algorithm-design-analysis-pennx-sd3x
Month 2
Week 1
Learn python for data science
https://www.youtube.com/watch?v=T5pRlIbr6gg&list=PL2-dafEMk2A6QKz1mrk1uIGfHkC1zZ6UU #### Math of Intelligence https://www.youtube.com/watch?v=xRJCOz3AfYY&list=PL2-dafEMk2A7mu0bSksCGMJEmeddU_H4D #### Intro to Tensorflow https://www.youtube.com/watch?v=2FmcHiLCwTU&list=PL2-dafEMk2A7EEME489DsI468AB0wQsMV
Week 2
Intro to ML (Udacity) https://eu.udacity.com/course/intro-to-machine-learning–ud120
Week 3-4
ML Project Ideas https://github.com/NirantK/awesome-project-ideas
Month 3 (Deep Learning)
Week 1
Intro to Deep Learning https://www.youtube.com/watch?v=vOppzHpvTiQ&list=PL2-dafEMk2A7YdKv4XfKpfbTH5z6rEEj3
Week 2
Deep Learning by Fast.AI http://course.fast.ai/
Week 3-4
Re-implement DL projects from my github https://github.com/llSourcell?tab=repositories
Additional Resources:
- People in ML to follow on Twitter - Join the “Wizards” Slack channel
Learn_Deep_Learning_in_6_Weeks
This is the Curriculum for “Learn Deep Learning in 6 Weeks” by Siraj Raval on Youtube
Overview
This is the curriculum for this video on Youtube by Siraj Raval
Week 1 - Feedforward Neural Networks and Backpropagation
- Read Part I of the Deep Learning Book found here
- Use this cheat sheet to help understand any math notation, found here
- Watch Build a Neural Net in 4 Minutes
- Read Neural Net in 11 lines
- Type out the neural network code yourself in a text editor, compile, and run it locally (using no ML libraries)
- Watch Backpropagation in 5 minutes
Week 2 - Convolutional Networks
- Watch the Convolutional Networks Specialization on Coursera, found here.
- Read all 3 lecture notes under Module 2 for Karpathy CNN course found here
- Watch my video on CNNs here and here
- Write out a simple CNN yourself (using no ML libraries)
Week 3 - Recurrent Networks
- Watch the Sequence Models Specialization on Coursera, found here
- Watch my videos on recurrent networks, here, here, and here
- Read Trask’s blogpost on LSTM RNNs found here
- Write out a simple RNN yourself (using no ML libraries)
Week 4 - Tooling
- Watch CS20 (Tensorflow for DL research). Slides are here. Playlist is here
- Watch my intro to tensorflow playlist here
- Read Keras Example code to quickly understand its structure here
- Learn which GPU provider is best for you here
- Write out a simple image classifier using Tensorflow
Week 5 - Generative Adversarial Network
- Watch the first 7 videos you see here
- Build a GAN using no ML libraries
- Build a GAN using tensorflow
- Read this to understand the math of GANs, but don’t worry if you dont understand it all. This is the bleeding edge here
Week 6 - Deep Reinforcement Learning
- Watch CS 294 here
- Build a Deep Q Network using Tensorflow
Learn_Data_Science_in_3_Months
Course Objective
This is the Curriculum for Learn Data Science in 3 Months by Siraj Raval on Youtube. After completing this course, start applying for jobs, doing contract work, start your own data science consulting group, or just keep on learning. Remember to believe in your ability to learn. You can learn data science, you will learn data science, and if you stick to it, eventually you will master it.
Find a study buddy
Join the #DataSciencein3Months (Private) channel in our Slack channel to find one.
Components
- 3 Projects
- 1 Weekly assignment. Pick 1 from the course for each week, do it in a weekend.
Course Length
- 12 Weeks
- 2-3 Hours of Study per Day
Tools Used
- Python, SQL, R, Tensorflow, Hadoop, MapReduce, Spark, GitHub,
Accelerated Learning Techniques
- Watch videos at 2x or 3x speed using a browser extension
- Handwrite notes as you watch for memory retention
- Immerse yourself in the community
Month 1 - Data Analysis
Week 1 - Learn Python
- EdX https://www.edx.org/course/introduction-python-data-science-2
- Siraj Raval https://www.youtube.com/watch?v=T5pRlIbr6gg&list=PL2-dafEMk2A6QKz1mrk1uIGfHkC1zZ6UU
Week 2 - Statistics & Probability
Week 3 Data Pre-processing, Data Visualization, Exploratory Data Analysis
Week 4 Kaggle Project #1
- Try your best at a competition of your choice from Kaggle.
- Use Kaggle Learn as a helpful guide
Month 2 - Machine Learning
Math of Machine Learning Cheat Sheets
Week 1-2 - Algorithms & Machine Learning
Week 3 - Deep Learning
- Part 1 and 2 of DL Book https://www.deeplearningbook.org/
- Siraj Raval https://www.youtube.com/watch?v=vOppzHpvTiQ&list=PL2-dafEMk2A7YdKv4XfKpfbTH5z6rEEj3
Week 4 - Kaggle Project #2
- Try your best at a competition of your choice from Kaggle. Make sure to add great documentation to your github repository! Github is the new resume.
Month 3 - Real-World Tools
Week 1 Databases (SQL + NoSQL)
- Udacity https://www.udacity.com/course/intro-to-relational-databases–ud197
- EdX https://www.edx.org/course/introduction-to-nosql-data-solutions-2
Week 2 Hadoop & Map Reduce + Spark
- Udacity https://www.udacity.com/course/intro-to-hadoop-and-mapreduce–ud617
- Spark Workshop https://stanford.edu/~rezab/sparkclass/slides/itas_workshop.pdf
Week 3 Data Storytelling
Week 4 Kaggle Project #3
- Try your best at a competition of your choice from Kaggle.