Data Science, Analytics, and AI for Business and the Real World ™

Preview this course

This course focuses on understanding all the basic theory and programming skills required as a data scientist, featuring 35+ practical case studies covering common business problems faced by them.
This course seeks to fill all those gaps in knowledge that scare off beginners and simultaneously apply your knowledge of data science and deep learning to real-world business problems.

Unlimited access to 750+ courses.
Enjoy a Free Trial. Cancel Anytime.

- OR -

30-Day Money-Back Guarantee
Full Lifetime Access.
251  on-demand videos & exercises
Level: Beginner
30hrs 50mins
Access on mobile, web and TV

What to know about this course

Right now, despite the Covid-19 economic contraction, traditional businesses are hiring data scientists in droves! Therefore, data scientist has become the top job in the U.S. for the last four years running. However, data science has a difficult learning curve.

This course seeks to fill all those gaps and has a comprehensive syllabus that tackles all the major components of data science knowledge. You will be using data science to solve common business problems throughout this course.

You will start with the basics of Python, Pandas, Scikit-learn, NumPy, Keras, Prophet, statsmod, SciPy, and more. You will learn statistics and probability for data science in detail. Then, you will learn visualization theory for data science and analytics using Seaborn, Matplotlib, and Plotly. You will look at dashboard design using Google Data Studio along with machine learning and deep learning theory/tools. Then, you will be solving problems using predictive modeling, classification, and deep learning. After this, you will move your focus to data analysis and statistical case studies, data science in marketing, and data science in retail.

Finally, you will see deployment to the cloud using Heroku to build a machine learning API. By the end of this course, you will learn all the major components of data science and gain the confidence to enter the world of data science. All the code files and the resource files are uploaded on the GitHub repository at

Who's this course for?

This course is designed for beginners in data science; business analysts who wish to do more with their data; college graduates who lack real-world experience; business-oriented persons who would like to use data to enhance their business; software developers or engineers who would like to start learning data science. Anyone looking to become more employable as a data scientist and with an interest in using data to solve real-world problems will enjoy this course thoroughly. No need to be a programming or math whiz; basic high school math will be sufficient.

What you'll learn

  • Look at machine learning algorithms with Scikit-learn
  • Create beautiful charts, graphs, and visualizations that tell a story with data
  • Understand common business problems and how to apply data science
  • Create data dashboards with Google Data Studio
  • Learn to apply data science in marketing and retail Integrate big data analysis and machine learning with PySpark.

Key Features

  • Explore 16 statistical and data analysis, and six predictive modeling and classifiers case studies
  • Work on four: data science in marketing and retail, and two time-series forecasting case studies
  • Dive into three Natural Language Processing and one PySpark big data case studies, and a deployment project.

Course Curriculum

About the Author

Rajeev Ratan

Rajeev Ratan is a data scientist with an MSc in artificial intelligence from the University of Edinburgh and a BSc in electrical and computer engineering from the University of West Indies. He has worked in several London tech start-ups as a data scientist, mostly in computer vision. He was a member of Entrepreneur First, a London-based start-up incubator, where he co-founded an EdTech start-up.

Later on, he worked in AI tech start-ups involved in the real estate and gambling sectors. Before venturing into data science, Rajeev worked as a radio frequency engineer for eight years. His research interests lie in deep learning and computer vision. He has created several online courses that are hosted on many global online portals.

40% OFF! Unlimited Access to 750+ Courses. Redeem Now.