I am strengthening my education in Data Science through a 6-month intensive Data Science Bootcamp at CodeOp. This bootcamp has a mission to cover fundamental concepts of Statistics and Machine Learning and Relational Databases:
Hands-on training using libraries in Python: NumPy, Pandas, Matplotlib, Seaborn, Scikit-learn
Hands-on working with Git, GitHub, Jupyter Notebook, Visual Studio Code (VSC), Python programming, and working in small groups for the assignments to improve team working skills.
Working on one individual and one group project based on real data.
Besides, I am learning more about Data Science concepts and fundamentals through different sources. DataCamp is a highly recommended source. I do a track called Data Scientist with Python:
Learning Python for data science and gain the career-building skills needed to succeed as a Data Scientist, from Data Manipulation to Machine Learning.
Working with real-world datasets to learn the Statistical and Machine Learning techniques needed to perform Hypothesis Testing and build Predictive Models.
An introduction to Supervised (and Unsupervised) Learning with Scikit-learn.
Apply all the skills to various projects and interactive exercises.
I also have very good Data Science and Python courses from Udemy.
To update my Math skills, I enrolled and passed a course, Data Science Math Skills by Duke University, on Coursera.
1- Follow my own progress along with the courses.
2- Provide all my projects in one place for job applications.
3- Having a great source of all that I have done and will do in my journey.
4- Create a great information source for people like me, future Data Scientists!