CPD
Here I would like to showcase all the resources that I have used for my CPD (Continuous Professional Development). I enjoy learning new things related to my career in different ways:
- Doing online courses from websites such as Coursera, Udemy, FreeCodeCamp;
- Reading textbooks on topics in Data Science, Statistics, and Programming;
- Attending and participating in live events;
You can see all the Data Science-related books that I’ve read on my Goodreads account, shelf _data-science.
Please note that this section is still being written, so there are many things that are not present here!
Machine Learning
| Resource | Description | Photo |
|---|---|---|
| Course Machine Learning Specialisation - DeepLearning.ai, Stanford (Coursera) |
This is an amazing comprehensive course that teaches both theoretical and practical aspects of building ML models. I believe that this might be the best course on ML out there and would highly recommend it! |  |
| Essential Math for Data Science - Thomas Nield (O'Reily) | While not as rigorous and comprehensive as other books on Data Science, this one is a relatively easy read that is perfect for revising challenging theoretical concepts in Machine Learning. |  |
| Grokking Machine Learning - Luis Serrano, Manning Publications | This book is an excellent introduction into the world of Machine Learning - it uses very simple examples to explain different ML algorithms and Gradient Boosting. I believe that this is the best book that a person can choose to start their journey into the world of ML. See my detailed review and error revision on Github |
 |
Data Analysis
| Resource | Description | Photo |
|---|---|---|
| Learning SQL - Alan Beaulieu | I liked this book as a revision resource for SQL. While well-written, I feel like it was lacking in the number of exercises. Additionally, it was using many subqueries instead of CTEs, which can require a skill to be able to write, but in the real world CTEs make the code much more readable. Overall, pretty good book, but definitely not the best. |  |
| Data Analysis with Python - freeCodeCamp | This is a simple introductory course from FreeCodeCamp that teaches the essentials of data cleaning, processing, and visualisation with Python libraries (Numpy, Pandas, Matplotlib). |  |
| Scientific Computing with Python - freeCodeCamp | This course improved my understanding of programming in Python and offered some challenging certification projects. |  |
Apart from the resources mentioned above, I really enjoyed doing exercises on SQL on Leetcode. The problem set is called SQL 50 - you can check it out on my Leetcode profile.
Databases
| Resource | Description | Photo |
|---|---|---|
| Relational Database - freeCodeCamp | Following the completion of this code, I learned the essentials of relational databases (in this case, PostgreSQL), different ways to connect to the databases, and write scripts in Bash that would interact with PostgreSQL. |  |