Data Science, Mathematics

Data science is an interdisciplinary field that uses scientific methods, processes, and algorithms to extract knowledge and insights from data. The field of data science has several subdivisions such as data mining, data transformation, data visualization, machine learning, deep learning, etc. As a scientific discipline, a data science task could be broken into 3 main stages:

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.

1. What is data science?

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…

Data Science

“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…

Data Science

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

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…

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.

Introduction

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…

I. Introduction

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

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.