Program Overview: 

This Data Scientist Master’s program, in collaboration with IBM, helps you master the concepts of data science. You will learn key technologies including R, Python, Tableau, Hadoop, and Spark. You will also gain an understanding of supervised and unsupervised learning models such as linear regression, logistic regression, clustering, dimensionality reduction, KNN, and pipelines required to start your career as a data scientist.

Program Highlights
  • 40s0+ hours of applied learning
  • 15+ real-life projects providing hands-on industry training
  • Industry-recognized certificates from IBM (for IBM courses) and Simplilearn
  • 30+ in-demand skills 
  • Portfolio-worthy capstone demonstrating mastered concepts 
Course Delivery Method: 

Online Bootcamp: Online self-paced video-based learning and live virtual classroom conducted by the industry’s leading coaches


To take this Data Scientist Master’s program you should have a basic understanding of statistics and any programming language.

Skills Covered: 
  • Exploratory data analysis
  • Descriptive statistics
  • Inferential statistics
  • Model building and fine-tuning
  • Supervised and unsupervised learning
  • Natural language processing
  • Ensemble learning
Learning Path
  • Lesson 1

    Statistics Essentials

  • Lesson 2

    R Programming for Data Science

  • Lesson 3

    Data Science Certification Training - R Programming

  • Lesson 4

    Python for Data Science

  • Lesson 5

    Data Science with Python

  • Lesson 6

    Machine Learning

View more

  • Lesson 7


  • Lesson 8

    Big Data Hadoop and Spark Developer

  • Lesson 9

    Data Science Capstone

Who Will Benefit 

This Data Scientist Master’s program is best suited for IT Professionals, analytics managers, business analysts, banking and finance professionals, marketing managers, supply chain network managers, beginners or recent graduates with bachelor’s or master’s degrees with an analytical frame of mind.

Key Learning Outcomes 
  • Gain an in-depth understanding of data structure and data manipulation 
  • Understand and use linear and non-linear regression models and classification techniques for data analysis 
  • Perform scientific and technical computing using the SciPy package and its sub-packages such as Integrate, Optimize, Statistics, IO, and Weave 
  • Gain expertise in mathematical computing using the NumPy and Scikit-Learn package
  • Understand the different components of the Hadoop ecosystem 
  • Learn to work with HBase, its architecture and data storage, learning the difference between HBase and RDBMS, and use Hive and Impala for partitioning 
  • Understand MapReduce and its characteristics, plus learn how to ingest data using Sqoop and Flume 
  • Master the concepts recommendation engine, and time series modeling and gain practical mastery over principles, algorithms, and applications of machine learning 
  • Learn to analyze data using Tableau and become proficient in building interactive dashboards
Certification Exam Eligibility

There is no certification exam available for this program however you may get certified in some of the courses which are part of this program. Please reach out to our admissions department at www.mtssedu.com/admissions for more information.

Career Outlook

Expected Growth (2019 – 2029)*
  • 15%
Annual Average US Salary*
  • $86,000 - $157,000
Demanding Fields
  • Informaon Technology
  • Finance
  • Retail
  • Real Estate
  • Engineering
  • Hospitality Management
  • Business Consulng
Job Opportunies for Professionals
  • IT Professionals
  • Analytics Managers
  • Business Analysts
  • Marketing Managers
  • Supply Chain Network Managers
  • Banking and Finance Professionals
  • Beginners or Recent Graduates
          in Bachelors or Master’s Degree

*Salary and job outlook information comes from the US Bureau of Labor Statistics and Projections Central. Employment outcomes are not guaranteed.

Tools covered