Develop your mindset and learn how to think like a senior data scientist. This course is a perfect opportunity for aspiring data scientists who wish to learn from the advice of a seasoned data science professional.
Data science is unique for its combination of several different knowledge bases and skillsets. To become a successful data scientist, you need such skills as critical thinking, problem-solving, programming, engineering, math, statistics, business acumen, communication, and project management. Bootcamps and university degrees certainly don’t teach or prepare you to utilize all these skills together. To be a great data scientist, you need to wear multiple hats and learn how to think like a product manager, a scientist, an engineer, or a businessperson—which is why becoming a data scientist is challenging. Think of this course as your opportunity to gain experience and advice from someone who has been on the job for several years and wants to spend time with you and share what he has learned as a senior data scientist.
This course gives invaluable advice to those who are just starting or about to begin studying data science. You’ll gain an understanding of the type of work you’ll do as a data scientist, why it’s an exciting and demanding job, the best way to build a project portfolio, and, most importantly, develop a mindset that helps you be successful on the job.
In this introductory section, you learn why data science is so unique and what it’s like to work in the field. The author introduces you to the importance of data science projects and how to build a project portfolio that stands out. He also discusses at length the various data science roles you can apply for and what type of mindset you should adopt to become a data scientist.
If you are a data scientist, you cannot plan for insights. So, instead of spending a lot of time up front on planning, you need to be flexible enough to adapt and change - whether it’s a change in assumption or a change in question. The love of experimenting is vital. Most individuals new to data science still crave planning typical for other activities. In this part of the course, you’ll learn how to address these challenges and re-wire how you think about work.
The concept of data as a wilderness is one of the most compelling reasons for using the term ‘data science’ instead of outdated terms like ‘data mining’. We focus on the scientific method in this part of the course. This is not a new topic, as scientists have conducted scientific research for centuries. The difference, however, is that today we live in a data jungle with significantly more data. This tremendous amount of data allows us to gain powerful knowledge without leaving our office or home. We must use the scientific method to get to data’s truth and valuable answers—there’s no way around that.
Student feedback
“A data scientist thinks like an engineer, a scientist, and a businessperson. This trifecta is a unique mindset to adopt and is what makes careers in data science so special. You don’t get a paycheck because you know 100 different algorithms. You get paid to solve real-world problems.”
Host of the “The Artists of Data Science” podcast
How to Think Like a Data Scientist to Become One
with Harpreet Sahota
