From the Arizona State University Master of Computer Science

Big Data MasterTrack® Certificate

Give your career a competitive edge in data mining techniques, data analytics, data visualization, and statistical machine learning from the #1-ranked school for innovation in the U.S.

The next session starts in January 2022. Apply by December 27, 2021. For details on applying, review the FAQ section.

Earn Credit Towards a Degree If you get a B or better on your first attempt in every course in this MasterTrack® Certificate, you will earn a university-issued certification, as well as satisfy the GPA requirement for the ASU Master of Computer Science degree program. Apply these credits to the Master of Computer Science at Arizona State University to begin the program with 9 of your 30 required credits completed. You must still meet all other admission criteria in order to be eligible for the degree program.

About this Online Certificate Program

Learn to navigate large, complex datasets through interactive exploration.

Skills you will gain

  • Data mining
  • Data visualization
  • Big data
  • Queries
  • Data processing
  • Spatial data
  • Nosql databases
  • Data models
  • Data classification
  • Data clustering
  • Deep learning
  • Reinforcement learning
  • Apache Spark
  • Python
  • Java
  • Course Mode

    100% online courses

  • Course Fee

    $4,500 USD

    Students pay by course. You will also be asked to pay an application fee when registering through the ASU website.

  • Duration

    6-9 months to complete

  • Course Level

    Intermediate Level

    You should have an understanding of the following topics: computer organization and architecture, discrete mathematics, data structures, and algorithms.

    Knowledge of high-level programming languages (e.g. Java) and scripting language (e.g. Python), relational database structures, and statistics is also recommended.

  • Projects

    3 hands-on projects

  • Course Language


    Contact our enrollment team at

  • Course Benefits

    Earn academic credit

    Receive 3 credits for every course.

What is a MasterTrack® Certificate?

With MasterTrack® Certificates, portions of Master’s programs have been split into online modules, so you can earn a high quality university-issued career credential at a breakthrough price in a flexible, interactive format. Benefit from a deeply engaging learning experience with real-world projects and live, expert instruction. If you are accepted to the full Master's program, your MasterTrack coursework counts towards your degree.

Master’s Degree Learning

Take an online module of a Master's degree program that features live expert instruction and feedback combined with interactive team-based learning.

Boost Your Career

Receive a university-issued MasterTrack Certificate from a top university that you can add to your resume and LinkedIn profile.

Build Your Portfolio

Demonstrate your skills through real-world projects and create work samples that help you stand out in your job search.

Earn Credit Towards a Degree

If you get a B or better on your first attempt in every course in this MasterTrack® Certificate, you will earn a university-issued certification, and can apply these 9 credits to the Master of Computer Science at Arizona State University.

Interactive Learning Experience

You'll learn through readings, videos, graded assignments, real-world applied projects, and live global classroom sessions.

Live Global Webinars

Live Global Webinars

Feedback from Instructors and Experts

Feedback from Instructors and Experts

Real-World Projects

Real-World Projects

3 Courses in this MasterTrack® Certificate

Take 3 of the 4 courses listed to earn your certificate.

Courses include:

  • Pre-recorded videos
  • Live sessions and office hours
  • Real-world projects
  • Peer collaboration
  • Web and mobile access

CSE 511 Data Processing at Scale

Database systems are used to provide convenient access to disk-resident data through efficient query processing, indexing structures, concurrency control, and recovery. This course delves into new frameworks for processing and generating large-scale datasets with parallel and distributed algorithms, covering the design, deployment and use of state-of-the-art data processing systems, which provide scalable access to data.

Specific topics covered include:

  • Efficient query processing
  • Indexing structures
  • Distributed database design
  • Parallel query execution
  • Concurrency control in distributed parallel database systems
  • Data management in cloud computing environments
  • Data management in Map/Reduce-based
  • NoSQL database systems

Learners completing this course will be able to:

  • Perform queries (e.g., SQL) and analytics tasks in state-of-the-art database systems
  • Apply leading-edge techniques to design/tune distributed and parallel database systems
  • Utilize existing NoSQL database systems as appropriate for specified cases
  • Perform database operations (e.g., selection, projection, join, and groupby) in state-of-the-art cluster computing systems such as Hadoop/Spark
  • Perform scalable data processing operations (e.g., selection, projection, join, and groupby) in cloud computing environments, including Amazon AWS

Read the full course brief>>

See all 4 Courses

Industry-relevant hands-on projects to build your portfolio

Activity Recognition Using Data Mining

15 hours total


  • Apply common data mining algorithms to discover relationships and patterns in large datasets.

Introduction to Statistical Graphics Using Data Visualization

20 hours total


  • Combine exploratory queries, graphics, and interaction to develop functional tools for exploratory data analysis and data visualization.

Hot Cell Analysis in Big Data

20 hours total


  • Demonstrate handling of computation intensive queries in big data.
See all 4 projects

What industry partners are saying

Linda Zaruches - Industry Recruiter and Alumni, GoDaddy
“GoDaddy has been recruiting ASU Computer Science students for the past 8 years. We love ASU students because they are passionate, smart, scrappy and dedicated to making a difference. Watching our ASU hires excel in their careers and make significant contributions to our success and our customers’ success is very rewarding. We look forward to continuing our long-standing relationship with ASU in hopes of hiring some of the best and brightest developers.”...
Megan Shaffer - Talent Acquisition Manager, Allstate
“Allstate keeps coming back to ASU Computer Science for the diverse talent pipeline. ASU offers many opportunities for us to engage with students, so we can hire efficiently and better serve our customers. We look forward to partnering for future career fairs, hackathons and student organization events.” ...


Mohamed Sarwat, Ph.D.

Mohamed Sarwat, Ph.D.

Assistant Professor of Computer Science; Director of the Data Systems (DataSys) Lab

Ross Maciejewski, Ph.D.

Ross Maciejewski, Ph.D.

Associate Professor at the School of Computing, Informatics & Decision Systems Engineering; Director of the Center for Accelerating Operational Efficiency, a Department of Homeland Security Center of Excellence

Ayan Banerjee, Ph.D.

Ayan Banerjee, Ph.D.

Assistant Research Professor at the School of Computing Informatics and Decision Systems Engineering

Frequently Asked Questions

More questions? Visit the Learner Help Center.

Coursera does not grant academic credit; the decision to grant, accept, or recognize academic credit, and the process for awarding such credit, is at the sole discretion of the academic institutions offering the MasterTrack® Certificate program and/or other institutions that have determined that completion of the program may be worthy of academic credit. Completion of a MasterTrack® Certificate program does not guarantee admission into the full Master’s program referenced herein, or any other degree program.