Data Analytics Essentials

Transform data into actionable insights and business solutions

Enquire: +1 512 877 8310


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MS - Business Analytics
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QS World University Rankings, 2022


Executive Education - Custom Programs
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Financial Times,

Why choose data analytics

The UT Austin Advantage

Taught by World-Renowned Experts
  • Designed by the world-renowned faculty at the University of Texas at Austin
  • Customized curriculum designed to build industry-valued skills
  • Live sessions by industry experts
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In-Demand Languages, Tools, and Skills
  • Python Foundations (NumPy, Pandas, Seaborn)
  • Business statistics
  • Data visualization (Tableau)
  • Querying data with SQL
  • Exploratory Data Analysis
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Job-Ready in Three Months
  • Apply your skills to three hands-on projects with specific industry-relevant applications
  • Enhance your resume and secure career opportunities with GreatLearning’s career support services
  • Work on projects alongside established data scientists and fellow learners worldwide
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Working Professional
Learn from world-renowned faculty from University of Texas at Austin
Career Support
Acquire in-demand skills in programming and tools for data analytics
Salary Hike
Get a hands-on learning experience with real world projects and cases
Industry Project
Be job ready with career guidance and a certificate of completion
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Data Analytics Essentials

Learn to leverage data and upskill in 3 months

Certificate from The University of Texas at Austin

zoom icon Data Analytics Essentials certificate by university of Texas at Austin

All certificate images are for illustrative purposes only. The actual certificate may be subject to change at the discretion of the University.

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Faculty Director, PGP-DSBA

H. Timothy (Tim) Harkins Centennial Professor Faculty Director, Center for Research and Analytics

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MS & PhD: Stanford University

For any feedback & queries regarding the program, please reach out to us at

GL Excelerate - Career Support

Designed to empower learners with everything they need to succeed in their careers, GL Excelerate is a career support program exclusively for our program learners.


Career Sessions

Interact personally with industry professionals to get valuable insights and guidance.

Curated Jobs
Curated Jobs

Resume & LinkedIn Profile Review

Present yourself in the best light through assets that truly showcase your strengths.

Interview Preperation
Interview Preperation

Interview Preparation

Get an insiders’ perspective to understand what recruiters look for.



Build an industry-ready portfolio to showcase your mastery of skills and tools.

Frequently Asked Questions

Program Details
What is the Data Analytics Essentials course from the University of Texas at Austin (UT Austin)?

The renowned experts from the McCombs School of Business at the University of Texas have carefully curated this course. Over the period of three months, students will grasp the essential foundational knowledge and skills needed to enter the modern analytical world.

What is the ranking of the University of Texas at Austin McCombs School of Business?

The university is ranked in the 6th position globally in Business Analytics according to the QS World University Rankings 2021. With 40+ postgraduate programs and 15 undergraduate programs listed in the top 10 nationwide, the U.S. News & World Report has consistently placed UT Austin among the top 20 public universities.

Why should I choose this Data Analytics course for beginners from UT Austin?

The McCombs School of Business at the University of Texas at Austin is a reputed business school at a renowned public research university. Through excellent instruction, hands-on learning, and the pursuit of pertinent, ground-breaking research, UT Austin develops ideas and cultivates principled leaders, preparing those who will mold tomorrow and address the most challenging issues.

With a proven track record of many successes, cutting-edge research, and teaching methods, students can be confident that they are learning from the best of the best.

What is unique about this Data Analysis course for beginners?

The Data Analysis beginners course is unique in the following aspects:


  • Students will obtain knowledge from professional data analysts with a variety of backgrounds, weekly one-on-one mentoring sessions, and frequent real-world case studies.

  • Through expert-led sessions, self-paced videos, three hands-on projects, and in-depth mentoring sessions, the course brings concepts related to dynamic data analytics to life.

  • Students will develop analytical skills through the curriculum that are in demand not just in data-related disciplines but also in a variety of other fields, including communication, business, management, healthcare, and many more.

What concepts and tools are covered in the course?

Students will get familiar with several in-demand concepts and tools in this course, including:


  • Excel

  • Python


  • Querying Data with SQL

  • Business Statistics

  • NumPy

  • Pandas

  • Seaborn

  • Data Visualization using Tableau

  • Exploratory Data Analysis

Who would be the faculty to teach this Data Analytics beginners course?


The renowned and highly esteemed faculty members of UT Austin and highly skilled business analysts across the globe will teach this program and guide students through the fundamentals of data analytics.


What exactly does mentored learning entail?

Students are instructed through a unique mentored learning approach that takes place in a micro-class of 10-15 students. These live sessions feature two-way voice and video communication.

Will the sessions be live or recorded?


The students will go through live and interactive sessions. But in addition to being live sessions, these sessions will also be recorded and uploaded on the LMS (Learning Management System) so that students who are unable to attend a session or who wish to study it later can do so by viewing the video.


Will I be awarded any certificate after completing the course?

Upon successfully finishing the course, students will receive a completion certificate in Data Analytics Essentials from the University of Texas at Austin.

Will I receive any career support after completing the course?

Yes, the students will receive career support from Great Learning, a part of BYJU’s group and India's reputed ed-tech platform for higher education and professional development.


The career support services are as follows:


  • Career Sessions: Students will engage in direct communication with industry experts to gain insightful advice.

  • Resume and LinkedIn Profile Review: The course will assist students in creating a top-notch resume that highlights their skills and prior work experience.

  • Interview Preparation: With our interview preparation classes, students can get a behind-the-scenes look at what hiring managers are looking for and learn how to ace interviews.

  • E-Portfolio: Students will discover how to create an industry-ready portfolio to demonstrate their proficiency with tools and skills.

Will I still have access to the learning materials after completing the course?

Yes. Since we think learning should be ongoing, we will make all the lectures and learning materials available to students for three years after they have finished the Data Analytics Essentials course.

How will I be assessed during the program?

The Data Analytics Essentials program is comprehensive, demanding, and follows a continual evaluation process. We assess a candidate's comprehension of the topics acquired through quizzes, assignments, and projects that involve experiential learning.

What is the duration of this Data Analytics online course for beginners?

The course duration is 3 months, which is held in micro classes and taught by highly experienced faculty members.

Eligibility Criteria
What are the eligibility criteria for this Data Analysis for beginners course?

The eligibility criteria for this course are as follows:


  • Recent graduates and early career professionals looking to acquire job-ready skills in the fields of business intelligence and data analytics can enroll in this course. The course trains and prepares students for a job role as a business analyst or data analyst.

  • Candidates who are looking to enter the world of data and leverage it to make analytical decisions across several industries.

  • Candidates who want to develop the fundamentals of data analysis over a condensed timeframe with a realistic resource investment.

Fee Related Queries
What is the course fee to pursue this Data Analytics Essentials program from UT Austin?


The fee to pursue this program is USD 2200. Interested candidates can pay through 3 interest-free installments.


[Contact our admissions office at +1 512 877 8310 for more details.]


What is the refund policy?

Please note that submitting the admission fee does constitute enrolling in the program and the below cancellation penalties will be applied:

1) Full refund can only be issued within 48 hours of enrollment


2) Admission Fee - If cancellation is requested after 48 hours of enrollment, the admission fee will not be refunded. 


3) Fee paid in excess of the admission fee: 

  1. Refund or dropout requests requested more than 4 weeks before the Commencement Date are eligible for a full refund of the amount paid in excess of the admission fee

  2. Refund or dropout requests requested more than 2 weeks before the Commencement Date are eligible for a 75% refund of the amount paid in excess of the admission fee

  3. Refund or dropout requests requested more than 24 hours before the Commencement Date are eligible for a 50% refund of the amount paid in excess of the admission fee

  4. Requests received after the Commencement Date are not eligible for a refund. 

  5. Cancellation must be requested in writing to the program office.

Admission queries
What is the admission process to pursue this Data Analysis course for beginners?

To enroll in this course, the applicants must meet the eligibility criteria mentioned earlier. The admission process for the eligible candidates is provided below:


  • Step-1: Register through an easy online application form.

  • Step-2: Take a quick screening call to ensure the course fits your goals.

  • Step-3: Once finalized, you can reserve your seat by paying the registration fee.


Note: Document verification is required prior to admission to the program.


What is the deadline to enrol in this Data Analytics course for beginners?

The admissions are closed after the required number of participants has registered for the upcoming batch. The few seats available for this course are subject to the first-come, first-served rule. Apply before time to secure your seats.

Cohort Start Dates

Great Learning-Online Center


15th Jul 2023

Still have queries? Contact Us

Please fill in the form and a Program Advisor will reach out to you. You can also reach out to us at or +1 512 877 8310

Application Closes 22nd Jun 2023

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Best Data Analytics Course for Beginners - The University of Texas at Austin (UT Austin)

Experienced professionals at the University of Texas at Austin (McCombs School of Business) have designed the Data Analytics Essentials program to facilitate a comprehensive understanding of the field in three months. Learners will gain the critical skills and expertise required to thrive in the contemporary analytical world.

The program is crafted to enable data analytics enthusiasts to interact and learn from highly skilled data analysts with diverse backgrounds, weekly one-on-one mentorship sessions, and industry-relevant, real-world case studies. It brings potent data analytics concepts to life through expert-led sessions, self-paced videos, three hands-on projects, and in-depth mentorship sessions. Learners will acquire the most in-demand analytical skills across various industries, including communication, business, management, healthcare, and several other sectors.

The UT Austin Advantage in this Data Analytics Program for Beginners

The University of Texas at Austin was founded in 1883 and now enrolls more than 51,000 students and 3,000 teaching faculty. UT Austin is known across the world as a pioneer in the fields of social science, business, technology, and science.

According to the QS World University Rankings 2021, the university is ranked 6th across the globe in business analytics. UT Austin has also continuously been ranked among the top 20 public universities by U.S. News & World Report, thanks to its 40+ postgraduate programs and 15 undergraduate programs that are among the top 10 in the United States.

Benefits of Learning the Fundamentals of Data Analytics from UT Austin

The curriculum combines coursework directed by industry experts with assistance from professional data analysts to ensure that learners succeed in this program and are job-ready from day one. 


  1. Recorded Lectures by World-Class Faculty

Learn from world-renowned faculty from UT Austin and a team of international data analytics experts.

  1. Mentorship Sessions with Industry Experts

Through weekly sessions, the program gives learners the opportunity to interact with highly knowledgeable mentors who can assist them in gaining practical experience. 

  1. Portfolio-Building Projects

Learners will work on hands-on projects, tests, and case studies that are pertinent to their industries and showcase their abilities to potential employers.


Key Learning Outcomes of the Data Analytics Program for Beginners


When learners complete this program, they will be able to:


  • Understand the technical, conceptual, and business aspects of the data analytics landscape.

  • Conduct exploratory data analysis using Excel, Python, SQL, and Tableau.

  • Query data in an SQL database to produce analytical data, business reports, and insights.

  • Acquire the fundamentals of databases and learn how to use them for managing, extracting, and manipulating data with SQL.

  • Learn how to use data visualizations for storytelling to enlighten business issues.

  • Gain familiarity with Python for analyzing data to implement in a variety of business problems.


Job Opportunities After Mastering Data Analytics Essentials


Upon successfully completing the course, learners may be eligible for a number of entry-level technical job roles, including:


  • Data Analyst: Data Analysts collect, analyze, and interpret data by identifying trends, patterns, and relationships in data sets and gain insights to help businesses make better decisions.

  • Product Analyst: Product Analysts work closely with product managers and other stakeholders to support the product development process by performing analysis of product requirements and market data.

  • Business Analyst: Business Analysts analyze the data and procedures of a company to help streamline its operations, develop reports, and make recommendations to the administration on how the company can improve its overall efficiency.

  • Analytics Engineer: Analytics Engineers work with data scientists to understand the business problems that need to be solved and identify the best ways to collect and analyze data for businesses.

  • Business Intelligence Analyst: Business Intelligence Analysts help companies make informed decisions by developing business intelligence models and plans that can lead to increased profits and growth.

  • Data Architect: Data Architects design and implement an organization’s data architecture, including the development and maintenance of data models, data management processes, and data governance policies.

  • Data Journalist: Data Journalists use various data analysis techniques, such as statistical analysis, data visualization, etc., to uncover and report stories they discover. 

  • Data Engineer: Data Engineers are responsible for the reliable and efficient movement of data within an organization. A data engineer work with data architects to design data models and build ETL (extract, transform, load) processes for moving data between systems.

  • Research Analyst: Research Analysts conduct primary and secondary research, analyze data, and develop insights to support decision-making. A research analyst works closely with data scientists and business analysts to understand business needs and design research plans.