Data Science RoadMap

For Datacamp courses we have access to it, if you don’t:

Github student pack gives you free access for 3 months.
You can google it, if you want more details

This track is divided into 3 phases..

1. Beginner: you get a basic understanding of data analysis, tools and techniques.
2. Intermediate: dive deeper in more complex topics of ML, Math and data engineering.
3. Advanced: where we learn more advanced Math, DL and Deployment.

Let's start...

Beginner

Estimated time: 1-1.5 months.

1. Python
   Basics-Udacity
   OOP-Datacamp
   Tutorial-Learn Python

2. Descriptive Stats
   Course-Youtube
   Course-Udacity
   

3. Numpy
   freeCodeCamp-Youtube
   Tutorial-CS231n
   Tutorial-Huawei Talent
   Docs
   

4. Pandas
   Tutorial-Kaggle
   Playlist-Youtube
   Course-Datacamp
   Docs
   

5. Data Cleaning: One of the MOST important skills that you need to master to become a good data scientist
   Read this-Medium
   Course-Datacamp
   Course-Kaggle
   Optional: Notebook-Kaggle
   

6. Data Visualization
   Course Matplotlib-Youtube
   C1Seaborn-Datacamp
   C2 Seaborn-Datacamp
   Course3-Datacamp
   Course4-Kaggle
   

7. EDA
   Course-Datacamp
   Notebook1-Kaggle
   Notebook2-CAT
   

8. SQL and DB
   Course1-Datacamp
   Course2-Datacamp
   

9. Regex
   Tutorial-Datacamp
   

10. Common tools
    Book-Git
    Course-Udacity
    

At The end of Beginner phase apply all what you've learned on a project.

Intermediate.

Estimated time: 2-3 months

You can advance your analytical skills before jumpying to ML by taking the following topics:

1. Advanced Statistics
   Book-Think Stats
   Book-Think Bayes
   Probability-Coursera
   Probability-Khan Academy
   Book-Probability
   

2. Time Series Analysis
   Course-Datacamp
   Docs-Prophet
   

3. APIs
   Tutorial-Dataquest
   Blog-Medium
   Tutorial-Rapidapi
   

4. Web Scraping & APIs
   Course1-Datacamp
   Course2-Dataquest
   Tutorial-Realpython
   Book
   

5. Advanced SQL
   Course1-Datacamp
   Course2-Datacamp
   Course3-ITI
   

---

ML Journey Begins from here:

1. Math for ML
   Specialization-Coursera
   Linear Algebra-Youtube
   Calculus-Youtube
   

2. ML
   Course1-Coursera
   Course2-Udacity
   Course3-Coursera
   Course4-Coursera
   Course5-Datacamp
   Book
   Project
   

3. Feature Engineering
   Tutorial-Kaggle
   Blog-Medium
   Book
   

4. Interpreting ML models more to be added here
   Docs-SHAP
   Course-Kaggle
   

After finishing this level apply to 2 or 3 good sized projects.

Advanced

Estimated time: 2-3 months

Advanced Analytical skills resources:

1. Advanced Statistics
   Inferential stats 1-Coursera
   Inferential stats 2-Coursera
   Bayesian Statistics 1-Coursera
   Bayesian Statistics 2-Coursera
   Mixture Models-Coursera
   

2. Advanced Data Science + apache spark
   Course-Coursera
   

3. Tableau & Power BI
   Tutorial-Datacamp
   Course1-Tableau
   course2-Datacamp
   Course3-ITI
   

---

DL Journey Begins from here:

1. Deep Learning
   Course-Coursera
   Book
   Github of the previous book

2. Tensorflow
   Course-Coursera
   

3. NLP
   Course-Coursera
   

4. Model Deployment More to be added here..
   Blog-Medium
   Course-Coursera
   Guided project
   

5. Probabilistic Graphical Models MORE yet to come in this section..
   Course-Coursera
   

More to come in this level...