Further Study Material

Data science is a vast field. There is always more to learn and explore. Especially, if you start browsing and looking for resources around the Internet, it won’t take long before you get information overload. The key is to not become overwhelmed.

Choose one or two courses or books at a time. Read, learn, understand, and apply the concepts before jumping on to the next, new, shiny thing. It is important to apply the concepts as you learn them, as we did throughout this course. It can be tempting to buy every book and start every course, but then you will more than likely never finish any of them. So rather than going all over the place, remember to focus and to learn by practicing.

Hence to keep it short and sweet, I am not going to give you a list of 100 resources! Here are my top two recommendations for you to go deeper and/or wider into the topics we have covered (and not covered):

📕 Data Science: Python Data Science Handbook

📕 Machine Learning: Hands-On Machine Learning with Scikit-Learn and TensorFlow