Use these questions to determine if data science is the right field for you

Image for post
Image for post
Photo by Christopher Robin Ebbinghaus on Unsplash

Data science skills have become increasingly more important for jobs that once had little to do with statistics, including marketing and business. Adding data science skills to your portfolio will give you an edge in your current role in the market this year. Before getting into data science, use the questions below to determine if data science is the right field for you.

Data Science is such a broad field that includes several subdivisions like data preparation and exploration; data representation and transformation; data visualization and presentation; predictive analytics; machine learning, deep learning, artificial intelligence, etc. There are three levels…


Peter Norvig’s (director of research at google) advice for data science newbies

Image for post
Image for post
Photo by Mitchell Luo on Unsplash

In 2021, professionals in the digital market space must be comfortable with data — period. They must know how to manipulate data, understand how it is collected, and analyze and interpret it. The future of decision making is grounded in data science.” — Wendy Moe, Professor of Marketing, University of Maryland

Data science skills have become increasingly more important for jobs that once had little to do with statistics, including marketing and business. Adding data science skills to your portfolio will give you an edge in your current role in the market this year.

If you are interested in adding…


An enormous amount of free learning resources in data science are available to anyone

Image for post
Image for post
Photo by Element5 Digital on Unsplash.

Many resources exist for the self-study of data science. In our modern age of information technology, an enormous amount of free learning resources are available to anyone, and with effort and dedication, you can master the fundamentals of data science.

There are two basic pathways to data science, the traditional college degree pathway, and the self-study pathway.

Traditional College Degree Pathway: Several top universities offer traditional graduate-level programs in data science. Because these are graduate-level programs, most will require an undergraduate degree in an analytical field such as physics, mathematics, accounting, business, computer science, or engineering. These programs typically have…


Data Science, Mathematics

Math skills will help you to avoid the pitfalls of using machine learning algorithms as black-box tools

Image for post
Image for post
Photo by Roman Mager on Unsplash

Can I become a data scientist with little or no math background?

What basic math skills are essential for data science practice?

There exist so many great packages or libraries available for Data Scientists to perform their work. Some of the most common packages for descriptive and predictive analytics include:

  • Ggplot2
  • Matplotlib
  • Seaborn
  • Scikit-learn
  • Caret
  • TensorFlow
  • PyTorch
  • Keras

However, mathematical skills are still essential in data science and machine learning because these packages will only be black-boxes for which you will not be able to ask core analytical questions without a solid math foundation. A sound math background is therefore…


4 platforms for portfolio building — GitHub, Kaggle, LinkedIn & Medium

Image for post
Image for post
Platforms for data science portfolio building. Image by Benjamin O. Tayo.

Making your big break into the data science profession means standing out to potential employers in a crowd of tough competition. An important way to showcase your skills and experience is through the presentation of a portfolio. Following these recommendations for developing your portfolio will help you network effectively and stay on top of an ever-changing field.

In the modern age of information technology, there is an enormous amount of free resources for data science self-study. As a matter of fact, you can even design your own data science curriculum from the innumerable amount of available resources. While knowledge acquired…


Computational thinking is about mastering the logical reasoning and flow of the project, irrespective of programming language used

Image for post
Image for post
Image by Benjamin O. Tayo

I. Introduction

There are several platforms and programming languages for data science and machine learning project implementation (see Figure 1 below).


For levels 1 and 2 data science, mastery of pandas, numpy, matplotlib, and scikit-learn is essential

Image for post
Image for post
Image by Benjamin O. Tayo

Introduction

For levels 1 and 2 data science, mastery of pandas, numpy, matplotlib, and scikit-learn libraries is essential. If you master these 4 packages, then you should be able to perform level 1 and 2 tasks using Python, as outline below.


Quantitative ability, problem-solving mindset, programming proficiency, effective communication, and team player skills

Image for post
Image for post
Photo by Sharon McCutcheon on Unsplash

I. Introduction

According to IBM, in 2019, businesses were creating and storing almost 2.5 quintillion bytes of data every day. Big Data is big business and businesses are swimming in oceans of valuable data. As one of the fastest-growing, multibillion-billion dollar industries, corporations, and organizations are trying to make the most out of the data they already have and determine what data they still need to capture and store. In addition, there continues to be an incredible need for data scientists to make sense of the numbers and uncover hidden solutions to messy business problems. …


Sometimes, you simply don’t have the tools in your toolbox for tackling a machine learning problem

Image for post
Image for post
Photo by Vincenzo Di Giorgi on Unsplash

An unsolvable machine learning problem is a problem that you can’t solve. This doesn’t mean that the solution to the problem doesn’t exist. It simply means that you don’t have the necessary tools in your toolbox for tackling the problem. As a data scientist or data science aspirant, you can only solve problems that you have the right set of tools for. That is why it is important for a data scientist to stay on top of his or her game and to continuously learn new skills.

As the field of data science is continuously changing, it is important that…


Careers, Data Science

With remote work becoming the norm, communication skills are crucial in data science

Image for post
Image for post
Photo by visuals on Unsplash

The pandemic has brought about unprecedented changes in the way companies conduct business. Several companies are now allowing employees to work remotely. Whether you are a seasoned data scientist or a data science aspirant still trying to get into the field, there are essential soft skills for remote work that you have to develop in addition to your hardcore technical skills. Strengthening your communication skills (including writing, speaking, and active listening) is extremely important.

In this article, we consider 6 essential soft skills for today’s virtual world.

The ability to articulate your ideas during a virtual meeting is a great…

Benjamin Obi Tayo Ph.D.

Physicist, Data Science Educator, Writer. Interests: Data Science, Machine Learning, AI, Python & R, Predictive Analytics, Materials Sciences, Biophysics

Get the Medium app

A button that says 'Download on the App Store', and if clicked it will lead you to the iOS App store
A button that says 'Get it on, Google Play', and if clicked it will lead you to the Google Play store