Roadmap Into Weeks.md

Roadmap Into Weeks

It's the same roadmap, but divided into weeks with an average studying rate of 6 hours per week.

This roadmap is divided into 4 stages:

1. Stage 1: you get a basic understanding of the prerequisites, data cleaning, and git.

2. Stage 2: learn visualizing, Tableau, SQL, and web scraping.

3. Stage 3: dive into ML and Math

4. Stage 4: where we learn DL, CV, and NLP.

You should make a task after each week, and some projects after each stage.

Stage 1

Week 1 :

Python-Basics (Full Course)
Task

Week 2:

Python Functions, Files, and Dictionaries
Task

Week 3:

Python-OOP (1st week only)
Descriptive stats
Task

Week 4:

Finish Python-OOP
Numpy (Full course)
Numpy DOC
Task

Week 5:

6 videos of Corey playlist
Task

Week 6:

7 → videos of Corey playlist
Git (session)
Task
Try to explore this data
notebook

Week 7:

Cleaning (data camp)
The Ultimate Guide to Data Cleaning
Cleaning Kaggle
Course Summary
Task(Try to clean this data)
useful repo for cleaning

Week 8:

Exploratory Data Analysis in Python (DataCamp Course)
Visualizing (data camp Matplotlib)
Matplotlib Tutorial
Task(Try to clean and visualize this data)
notebook

Stage 2

Week 9:

Visualizing Intro to seaborn (data camp)
Intermediate in seaborn(data camp)
Improving Your Data Visualizations in Python
Task(Try to clean and visualize this data)
notebook

Week 10:

Ask Questions (from Google specialization)
Task

Week 11:

Tableau and visualizing (from Google specialization)
Task(Create a Dashboard with tableau )

Week 12:

Intro to DB
Intro to SQL
Notebook
Task (Try to solve the following queries)
1 -https://www.hackerrank.com/challenges/select-all-sql?isFullScreen=true
2- https://www.hackerrank.com/challenges/japanese-cities-attributes/problem?isFullScreen=true
3- https://www.hackerrank.com/challenges/weather-observation-station-3/problem?isFullScreen=true
4- https://www.hackerrank.com/challenges/weather-observation-station-12?isFullScreen=true
5- https://www.hackerrank.com/challenges/binary-search-tree-1/problem?isFullScreen=true

Week 13:

Intro to web scraping
Web scraping

Task(Sacrap the following website and collect, Job title, Job skills, Job type (Full Time / Part Time), Company name, Company location and Post time )

Week 14:

Linear Algebra Or
preprocessing 1
preprocessing 2
preprocessing 3

Stage 3

Week 15 :

Inferential Stats

Week 16 :

Intro for Machine Udacity Course
Calculus Course (week 1,2,3)

Week 17 :

Supervised Machine Learning Andrew (week 1)
Calculus Course (week 4,5)
optional MIT Lectures

Week 18 :

Supervised Machine Learning Andrew (week 2)
Calculus Course (week 6)
optional Machine Learning (Dr Hamed Tizhoosh)

Week 19 :

Supervised Machine Learning Andrew (week 3)

Week 20 :

Advanced Learning Algorithms Andrew (week 1)

Week 21 :

Advanced Learning Algorithms Andrew (week 2)

Week 22 :

Advanced Learning Algorithms Andrew (week 3,4)

Week 23 :

First 2 weeks inUnsupervised Learning, Recommenders, Reinforcement Learning Andrew

Week 24 :

Finish Unsupervised Learning, Recommenders, Reinforcement Learning Andrew

Week 25 :

First 2 chapters in Hands on ML book use the following to get the book (56098000000101358 card number VQQy!Ng5DhR8j5i password )
Hegab Playlist

Week 26 :

Chapters 3,4 in Hands on ML book use the following to get the book (56098000000101358 card number VQQy!Ng5DhR8j5i password )
Hegab Playlist

Week 27 :

Chapters 5,6 in Hands on ML book use the following to get the book (56098000000101358 card number VQQy!Ng5DhR8j5i password )
Hegab Playlist

Week 28 :

Chapters 7,8 in Hands on ML book use the following to get the book (56098000000101358 card number VQQy!Ng5DhR8j5i password )
Hegab Playlist

Week 29 :

Chapter 9 in Hands-on ML book use the following to get the book (56098000000101358 card number VQQy!Ng5DhR8j5i password )
Hegab Playlist
First part in Probability

Week 30 :

Finish Probability

Stage 4

Week 31 :

First 2 Weeks Neural Networks course

Week 32 :

Finsh Neural Networks course

Week 33 :

First week Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization

Week 34 :

Second week Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization
Introduction to Deep Learning in Python

Week 35 :

Finish week Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization

Week 36 :

Structuring Machine Learning Projects Course

Week 37 :

Chapter 1,2,3 in Deep Learning with python use the following to get the book (56098000000101358 card number VQQy!Ng5DhR8j5i password )

Week 38 :

Chapter 4,5 in Deep Learning with python use the following to get the book (56098000000101358 card number VQQy!Ng5DhR8j5i password )

Week 39 :

Chapter 6,7 in Deep Learning with python use the following to get the book (56098000000101358 card number VQQy!Ng5DhR8j5i password )

Week 40 :

Convolutional Neural Networks Week 3, Week 4

Week 41 :

Chapter 8,9 in Deep Learning with python use the following to get the book (56098000000101358 card number VQQy!Ng5DhR8j5i password )

Week 42 :

Sequence Models Week 1, Week 2

Week 44 :

Sequence Models Week 3, Week 4

Week 43 :

Chapter 10,11 in Deep Learning with python use the following to get the book (56098000000101358 card number VQQy!Ng5DhR8j5i password )

Week 44:

Chapter 12,13 in Deep Learning with python use the following to get the book (56098000000101358 card number VQQy!Ng5DhR8j5i password )

More to be added...