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Data Analytics Essentials

Data Analytics Essentials

Master data analytics applications and secure a future-ready career

Application closes 19th Jun 2025

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Program Outcomes

Advance your career in Data Analytics

Become a data analytics expert

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    Understand data analytics from business, technical, and conceptual aspects

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    Analyze and visualize data using Excel, SQL, Python, and Tableau

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    Query and manage databases using SQL to generate insights and reports

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    Solve business problems with data storytelling and end-to-end Python analytics

Earn a certificate of completion

  • ranking 6

    #6 in MS - Business Analytics

    QS World University rankings, (2024)

  • ranking 6

    #6 in Executive Education - Custom Programs

    Financial Times (2022)

  • U.S. News & World Report, 2024

    #1 (U.S., Big Data Management) in MS Business Analytics

    Eduniversal (2024)

  • the financial engineer

    #6 in MS Business Analytics

    The Financial Engineer Times (2024)

Key program highlights

Why choose the data analytics essentials program?

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    Learn from world’s top university

    Earn a certificate from a world-renowned university, taught by the esteemed faculty

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    Industry-ready curriculum

    Learn the foundations of Python, GenAI, Data Visualization and more from top faculty. Gain valuable insights and apply your skills.

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    Learn at your convenience

    Gain access to content online, including lectures, assignments, and live webinars which you can access anytime, anywhere

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    3 hands-on projects

    Work on projects alongside established data scientists and fellow learners worldwide

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    Get expert mentorship

    Interact with mentors specialised in Data Analytics and get guidance to complete and showcase your projects

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    Personalized program support

    Get 1:1 assistance from a Program Manager. Access GL Community, project discussion forums and peer groups

Skills you will learn

Data Analysis with Excel

Descriptive Statistics

Python Programming

Data Transformation with Pandas and Numpy

Exploratory Data Analysis (EDA)

Data Visualization with Seaborn and Tableau

Interactive Dashboard Creation

PowerBI

Generative AI and ChatGPT Applications

Storytelling with Data

SQL Querying and Data Management

Data Analysis with Excel

Descriptive Statistics

Python Programming

Data Transformation with Pandas and Numpy

Exploratory Data Analysis (EDA)

Data Visualization with Seaborn and Tableau

Interactive Dashboard Creation

PowerBI

Generative AI and ChatGPT Applications

Storytelling with Data

SQL Querying and Data Management

view more

Secure top data analytics jobs

  • 11.5 million

    new jobs by 2026

  • Up to $110K

    avg annual salary

  • $105 million

    mkt value by 2027

  • 92%

    orgs use data

Careers in Data Analytics

Here are the ideal job roles in Data Analytics:

  • Data Analyst

  • Product Analyst

  • Business Analyst

  • Analytics Engineer

  • BI Analyst

  • Data Architect

  • Data Engineer

  • Data Journalist

  • Research Analyst

  • Data Scientist

Our alumni work at top companies

  • Overview
  • Career Transitions
  • Why GL
  • Learning Journey
  • Curriculum
  • Projects
  • Tools
  • Certificate
  • Faculty
  • Reviews
  • Career support
  • Fees
  • FAQ
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This program is ideal for

The Data Analytics Essential certificate program is designed for professionals looking to develop essential data analytics skills. It equips participants with the ability to interpret data, generate insights, and apply data-driven solutions in their careers or businesses.

  • Professionals Seeking Data-Driven Insights

    Designed for those looking to use data for strategic decision-making and business impact.

  • Career Changers Moving Into Analytics

    Suitable for individuals transitioning into data-focused roles such as data or business analysts.

  • Entrepreneurs & Consultants

    Helps business owners and consultants integrate data analytics into their strategies.

  • Aspiring Data Enthusiasts

    Suited for professionals looking to develop foundational data analytics skills for career growth.

Upskill with one of the best data analytics programs

  • Texas McCombs Programs

    Other Courses

  • Certificate

    hands upCertificate from the University

    hands downNo university certificate

  • Gen AI modules

    hands upExtensive coverage of Gen AI topics

    hands downLimited coverage

  • Live mentored learning

    hands upLive interactive online classes with industry professionals 

    hands downLimited to no live classes

  • Career support

    hands upYes, with ePortfolio and profile review

    hands downNo career support

  • Hands-on projects

    hands up3 industry projects

    hands downFewer projects

  • Dedicated Program support

    hands upDedicated support to complete your course

    hands downLimited support

Experience a unique learning journey

Our pedagogy is designed to ensure career growth and transformation

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    Learn with self-paced videos

    Learn critical concepts from video lectures by faculty and data analytics experts

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    Engage with your mentors

    Clarify your doubts and gain practical skills during the weekend mentorship sessions

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    Work on hands-on projects

    Work on industry-guided projects and apply the concepts & tools to solve business problems

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    Get personalized assistance

    Our dedicated program managers will support you whenever you need

Get an exclusive free preview of the course

Explore faculty videos and mentorship sessions. Get insights into relevant case-studies and projects.

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Ace Power BI Certification

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Ace PL-300 certification*

Prepare for PL-300 Certification Exam with:

  • Live Virtual Classes with Microsoft Certified Instructors

  • Hands-on Learning and Academic Support

  • Exam Preparation Guide

  • Hands-on Projects

*Delivered by Great Learning in collaboration with Microsoft

Curriculum

Developed by a leading university, this core curriculum of the data analytics essentials course covers foundational concepts and major skills and tools required to excel as a data analyst.

Pre-work

Here, we will quickly learn all the prerequisites required to learn the fundamentals of data analytics, such as Excel, Python Programming, and Descriptive Statistics.

Introduction to Excel

The first module of this data analytics course for beginners will cover the basics of Microsoft Excel. Students will learn data analysis essentials using Excel to create and format spreadsheets, along with CSV, tables, formulae, sorting, filtering, and much more.

  • Why Excel? What are the advantages of Excel?

Here, students will learn why Excel is a powerful spreadsheet application for analyzing and manipulating data and the advantages of using Excel for business and personal use.

  • CSV File Format

CSV files can be used with almost any spreadsheet program, such as Microsoft Excel, Apache Openoffice Calc, or Google Sheets. Here, students will learn how to use CSV for exchanging data between different applications.

  • Tools, Ribbons, Commands

In this, students will learn how to add functionality to a workbook and make working with data easier using tools, ribbons, and commands available in Excel.

  • Cell Referencing

This topic will teach students the process of cell referencing, a powerful feature in Excel that allows them to link data from multiple sheets and workbooks.

  • Tables

This topic will teach students how to implement tables in Excel to organize data and make it easy to view and understand.

  • Basic Arithmetic Functions (+,-,*,/)

This topic will make students familiar with implementing essential arithmetic functions to create more complex formulas that will unlock the power of Excel for data analysis needs.

  • Date Functions

This topic will familiarize students with implementing date functions using different formats in Excel.

  • Sorting

Here, students will learn how to sort data, where they can organize data in a way that makes it easier to find the information they need and to see relationships between different pieces of data

  • Filtering

Here, students will learn how to filter data, a powerful way in data analysis where they can easily view subsets of their data by hiding the rows that don't meet their criteria.

  • IF ELSE

The IF-ELSE function in Excel is a handy tool that allows us to perform different actions depending on whether a condition is met or not. This can be particularly useful when we have a large dataset and want to perform different analyses depending on specific criteria.

Descriptive Statistics

This module will cover the basic concepts of descriptive statistics, including measures of central tendency (mean, median, and mode) and measures of dispersion (range, variance, and standard deviation).

  • Seeing patterns in the data

Here, students will learn how to identify and analyze patterns in the data with the assistance of descriptive statistics.

  • Sample and Population

Here, students will gain an understanding of several concepts in probability, such as sample and population.

  • Central Tendency (Mean, Median, Mode)

This topic will make students familiar with measures of central tendency (mean, median, and mode) to help them calculate the average, find the median value of a dataset, and find the most frequent value.

  • Dispersion (Range, Variance, Standard Deviation)

This topic will make students familiar with measures of dispersion (range, variance, and standard deviation), which is essential for analyzing data sets because it can give us insights into the spread of the data.

  • Five-point Summary

In this topic, students will understand the five-point summary in descriptive statistics.

Data Analytics Foundations

Moving on to the next module of this data analytics essentials course, students will understand several fundamentals of data analysis, such as lifecycle, data pipeline, and insights generation using Excel, and apply these techniques to real-world data sets.

Analytics Life Cycle - An end to end use case

Industry 4.0 is the term used to describe the fourth industrial revolution, and data is the lifeblood of Industry 4.0. In this module, students will explore the world of data and how data is critical for the industrial revolution.

  • Introduction to Analytics Lifecycle

In this chapter, students will go through the various phases involved in the data analytics lifecycle.

  • Data sources and Databases

Data sources are the information repositories that hold the data sets that analysts utilize to perform their work.

  • A typical Data Pipeline

This chapter will familiarize students with the data pipeline, a series of steps to ingest, transform and analyze raw data.

  • Insight generation and Recommendation

Here, students will familiarize themselves with the process of analyzing data to discover trends and patterns that can be used to generate new insights and make recommendations.

  • End-to-end Business Case Study Demo

Here, students will go through a hands-on demo of an end-to-end business case study.

Generating Insights using Excel

In this module, students will explore the process of generating insights in multiple ways using Excel, such as tables, tabs, charts, and descriptive statistics.

  • Pivot Tables

This topic will make students understand pivot tables, which allow them to quickly summarize large amounts of data in a concise, easy-to-understand format.

  • Sorting Data in Pivot Tables

Here, students will learn how to sort data in pivot tables, where they can sort by values, by column, by row, and by multiple columns and rows.

  • Filtering Data in Pivot Tables

Here, students will learn how to filter data in pivot tables, where they can filter by date, product, customer, or any other entity.

  • Analyse Tab

Here, students will learn how to work with the analyze tab in Excel, which allows them to perform various statistical analyses on their data, like calculating means, standard deviations, percentiles, etc. They can also use the tab to create charts and graphs to visualize their data.

  • Exploring charts

In this topic, students will explore a variety of charts available in Excel to visualize data sets in multiple formats.

  • Descriptive Statistics

This chapter will help students analyze and understand diverse data sets in Excel with the aid of descriptive statistics.

Data Analytics with SQL

Heading into the next chapter, students will learn everything they need to know about how to use SQL to perform data analysis effectively. By the end, they’ll be able to confidently query databases and make sense of data like a pro!

Querying data with SQL

Querying data with SQL allows us to find and manipulate data in our database quickly. In this module, students will learn how to write and understand SQL queries to retrieve data from any database.

  • Importing a Database

Here, students will learn the process of importing a database into MySQL.

  • Introduction to RDBMS

This topic will introduce students to RDBMS, a relational database management system to create, store, update, and delete data in a relational database.

  • Selecting data

When working with data stored in a MySQL database, it is often necessary to select specific data in order to work with it. Here, students will learn how to select data in a variety of ways using the SELECT statement.

  • Filtering data

When working with databases, it is often necessary to filter data to return only the rows that meet specific criteria. Here, students will learn how to filter data and make their queries more specific using the WHERE clause.

Advanced Querying to extract business insights

Advanced querying encompasses a variety of techniques that allow a user to manipulate data in order to answer complex business questions. In this module, students will learn the process of advanced querying to extract business insights.

  • Aggregating data

Students will get familiar with data aggregation in SQL, a process of combining data from multiple tables into a single table, where a calculation is performed on a set of values and returns a single value.

  • Joining data

Students will familiarize themselves with combining data from two or more tables into a single table using the JOIN command.

  • Window Functions

Here, students will learn how to identify values in a collection of rows and provide a single result for each row, which is called the window function.

  • Order-of-Execution

Students will be introduced to the order-of-execution technique, which defines the specific order in which the clauses, expressions, and operators in a statement are evaluated.
 

  • Extracting data to Excel to perform data analysis

Enhancing Query Proficiency

Subqueries allow one to nest queries within other queries, enabling more complex and flexible data manipulation. This module will equip participants with advanced techniques for filtering data based on conditional expressions or calculating derived values to extract and manipulate data dynamically.

Project Week

Once students are done with the fundamentals of data analytics, this data analysis course for beginners will provide students with the first hands-on project on the topics learned so far.

Data-driven Insights using Python

This chapter teaches students how to use Python to gain insights from data. The course will cover how to use Python to read data from a variety of sources, how to process that data to extract useful information, and how to visualize the data to enable decision-making.

Introduction to Python Programming

This module will give students a comprehensive introduction to the Python programming language, covering topics like Google Colab, variables, data types, data structures, conditional statements, loops, and functions.

  • Setting up Google Colab

Google Colab is a free notebook environment for writing and executing code. Students will learn how to set up and work with Google Colab in this section.

 

  • Variables

Here, students will learn how to work with variables in Python to store values and retrieve them later.

  • Data Types

Here, students will understand data types, which define the type of data that a variable can hold. There are several built-in data types in Python, including integers, floats, and strings, among others.

  • Data Structures

Python's standard library provides a wide range of data structures that can be used to store and efficiently organize data. The most commonly used data structures are lists, tuples, dictionaries, and sets.

  • Conditional Statements

This topic will familiarize students with conditional statements that help them execute the code only if the specified condition is met.

  • Loops

The concept of loops will be taught to the students in this chapter. Loops can execute a block of code continually until a specific condition is met, such as computing the sum of two integers or displaying multiplication or other tables, among other things.

  • Functions

This chapter will help students understand and use Functions using Python programming so that they may reuse code.

Data Transformation using Numpy and Pandas

Numpy is a powerful library for performing numerical operations on arrays and matrices. At the same time, Pandas is a library for working with data frames, which are similar to tables in a relational database. In this module, we'll explore how to use these two libraries to perform various data transformation tasks.

  • Numpy Arrays

A Numpy array is a multidimensional array of objects of the same type, and this topic will teach students how to perform numerical operations efficiently using Numpy arrays.

  • Numpy Functions

This article will make students familiar with various Numpy functions that can assist them in speeding up their code.

  • Indexing

Students will learn how to find and retrieve data from a given data structure using Indexing in this topic.

  • Accessing

Here, students will learn how to access data from a Python project using the dot (.) operator.

  • Pandas Series

In this topic, students will understand how to hold several data types, such as numbers, strings, etc., using a one-dimensional array-like object, i.e., the Pandas Series.

  • Pandas Dataframes

Here, students will gain an understanding of Pandas Dataframes, which are two-dimensional, size-mutable, potentially heterogeneous tabular data structures with labeled axes (rows and columns).

  • Saving Loading

Here, students will explore the process of saving and loading files in multiple formats using the Pandas library.

  • Merging dataframes

This topic will familiarize students with the process of combining/merging two or more dataframes into a single dataframe with the help of specific methods.

  • Pandas Functions

This topic will familiarize students with various Pandas functions that are widely implemented in numerous applications of data science and machine learning.

Exploratory Data Analysis

Exploratory Data Analysis, also known as EDA, uses visual techniques to help us find patterns and insights frequently inside specific data. This module will explain EDA using Python in-depth.

  • Data Sanity Checks

This topic will make students understand the significance of performing sanity checks to ensure that the data is clean and ready for analysis while working with data.

  • Univariate Analysis

The students in this topic will gain an understanding of how to perform statistical comparisons using univariate analysis.

  • Bivariate Analysis

The students in this topic will gain an understanding of how to perform statistical comparisons using bivariate analysis.

  • Missing Value Treatment

This topic will familiarize students with the number of ways to deal with missing values when performing exploratory data analysis.

  • Outlier Detection

This topic will familiarize students with the number of ways to detect outliers that can help identify problems and patterns in data for further analysis.

Project Week

Once students are done with the data analysis essentials, this data analyst course for beginners will provide students with the second hands-on project on the topics learned so far.

Self-paced Module

Gain an understanding of what ChatGPT is and how it works, as well as delve into the implications of ChatGPT for work, business, and education. Additionally, learn about prompt engineering and how it can be used to fine-tune outputs for specific use cases.

Generative AI

This course provides you with an overview of what ChatGPT is and how it works, business applications of ChatGPT, and an overview of other generative AI models/tools via demonstrations

  • ChatGPT - Overview
  • ChatGPT - Business Applications
  • Generative AI Demonstrations

Data Visualization using Tableau

In this course, you will learn how to read, explore, and effectively visualize data using Tableau and tell stories by analyzing data using Tableau dashboards.

  • Storytelling with Data
  • Creating Interactive Dashboards

Career support: Portfolio review and interview preparation sessions

The Data Analytics Essentials program from University of Texas at Austin and Great Learning assists you to showcase your portfolio and be on top of employer preferences with resume and Linkedin portfolio review sessions and interview preparation guidance. You can also add the projects worked on during the program to your portfolio and enhance your skill competency.

Certificate of completion from the University and 4.5 Continuing Education Units (CEUs)

Upon completion of the program, earn a certificate of completion from the University of Texas at Austin McCombs School of Business.

End of Data Analytics Essentials Program by Texas McCombs

Start of PL-300 Certification Training

This curriculum is optimally designed with the outcome to prepare you for the Microsoft Power BI Data Analyst PL-300 certification exam.

Prepare Data for Analysis with PowerBI

This module aims to equip participants with the skills to prepare data from various sources to harness the potential of Power BI for data analysis and visualization. Participants will start by exploring the Power BI interface and its features, learn how to connect to data from various sources, get introduced to basic data modeling concepts followed by Power Query for data preparation, and explore advanced data modeling techniques to get the data ready for analysis and deriving actionable insights from their data. 

(PowerBI interface and features, Connecting to data from various sources, Creating visualizations and reports, Basic data modeling, Power Query for data preparation, cleaning, and transformation, Creating relationships between data tables, Advanced data modeling techniques)

Model Data with PowerBI

This module delves into data modeling techniques within Power BI, equipping participants with the skills to design and implement efficient data models. Participants will explore various data modeling approaches in Power BI, explore designing data models using the star schema and other relevant data structures, utilize DAX (Data Analysis Expressions) commands to create sophisticated calculations and measures, and build comprehensive reports and visualizations using queries and analytical techniques, helping participants transform raw data into actionable insights and compelling visual narratives. 

(Data modeling approaches in PowerBI, Designing data models using star schema and data structures, DAX commands for creating calculations and measures, Building reports and visualizations using queries and analytics)

Advanced Data Modeling with PowerBI

This module focuses on advanced techniques in Power BI to enhance data analysis and model management. Participants will explore advanced time intelligence calculations using DAX functions, implement strategies for optimizing performance in Power BI models and reports, improve query performance with DirectQuery and variables, and gain insights into securing data access and controlling model objects, ensuring data integrity and compliance with organizational policies. 

(Advanced time intelligence calculations using DAX functions, Optimizing performance in PowerBI models and reports, Improving query performance with DirectQuery and variables, Managing data complexity with cardinality reduction and aggregations, Securing data access and controlling model objects)

Build PowerBI Visuals and Reports

TThis module equips participants with the skills to design and create impactful reports that effectively communicate insights and engage users. Participants will cover the key principles involved in understanding user needs and design reports that address those needs for clear and effective communication. They’ll also gain insights into designing and customizing report layouts and visualizations to present data in the most meaningful way, use report objects and filtering techniques to enhance the functionality and interactivity of their reports, and learn to enable user interaction and real-time data exploration, allowing users to dive deeper into the data and extract valuable insights on the fly. 

(Understanding user needs and designing reports for effective communication, Creating engaging and informative reports with a focus on user experience, Designing and customizing report layouts and visualizations, Using report objects and filtering techniques to enhance report functionality, Enabling user interaction and real-time data exploration)

Building Advanced Visuals and Reports Using PowerBI

This module is tailored to enhance participants' skills in designing and creating advanced reports using various techniques and best practices. Participants will learn how to design detailed, interactive reports emphasizing the importance of visual storytelling, explore methods to optimize report performance and usability, and learn to create reports tailored for specific use cases, such as mobile devices and paginated reports, ensuring versatility and adaptability in various contexts. 

(Designing detailed and interactive reports for in-depth analysis, Creating engaging and informative reports with visual storytelling, Optimizing report performance and usability, Analyzing and visualizing data with advanced techniques, Creating reports for specific use cases, such as mobile devices and paginated reports)

Manage Workspaces and Datasets in PowerBI

This module provides participants with the knowledge and skills needed to effectively deploy and manage Power BI solutions within an organization. Participants will learn best practices for securing and protecting Power BI data and models, techniques for monitoring and troubleshooting Power BI performance and issues, implementing row-level security and data governance to control and manage data access, and creating and managing dashboards for data exploration and insights, empowering them to design interactive and insightful dashboards that facilitate informed decision-making and data-driven exploration. 

(Deploying and managing PowerBI solutions, Securing and protecting PowerBI data and models, Monitoring and troubleshooting PowerBI performance and issues, Implementing row-level security and data governance, Creating and managing dashboards for data exploration and insights)

Hands-on learning & projects

Work on projects and implement your skills with established data experts and fellow learners from around the world

  • 20

    learners group

  • 2-way

    audio-video interaction

  • 3

    real-world projects

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Retail

Improving customer experience with EDA

About the Project

Analyze customer order data to understand restaurant demand and enhance user experience through exploratory data analysis.

Skills you will learn

  • Python basics
  • Data manipulation with Pandas and NumPy
  • Data visualization using Seaborn/Matplotlib
  • Exploratory Data Analysis
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Automobile

Analyzing after-sales feedback with SQL

About the Project

Query and manipulate SQL database to generate business insights and create a quarterly report for decision-making.

Skills you will learn

  • SQL querying and filtering
  • Aggregation and joins
  • Subqueries and window functions
  • Report generation for business insights
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Entertainment

Creating personalized dashboard with PowerBI

About the Project

Analyze viewer preferences and promote classic movies to expand the customer base for an online entertainment database

Skills you will learn

  • Data Visualization
  • PowerBI Filters and DAX Commands
  • PowerBI Calculations
  • PowerBI Slicer and Navigator Actions
  • PowerBI Filter Actions

Master in-demand data analytics tools

Learn relevant skills, tools, and concepts

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    Python

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    Excel

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    RDBMS

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    Business statistics

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    Tableau

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    powerBI

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    SQL

  • And More...

Earn a Professional Certificate in Data Analytics

Get a certificate from one of the top universities in USA and showcase it to your network

certificate image

* Image for illustration only. Certificate subject to change.

Meet your faculty

Learn new data analytics skills each week from top faculty and expert business analysts

  • Dr. Daniel A Mitchell - Faculty Director

    Dr. Daniel A Mitchell

    Clinical Assistant Professor, Department of Information, Risk & Operations Management, McCombs School of Business, The University of Texas at Austin

    Research Director, Center for Analytics and Transformative Technologies

    15+ years of experience in financial engineering and quantitative finance.

    Know More
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  • Dr. Kumar Muthuraman - Faculty Director

    Dr. Kumar Muthuraman

    Faculty Director, Center for Analytics and Transformative Technologies, McCombs School of Business, the University of Texas at Austin

    Faculty Director, Center for Analytics and Transformative Technologies

    21+ years' experience in AI, ML, Deep Learning, and NLP.

    Know More
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  • Mr. R Vivekanand - Faculty Director

    Mr. R Vivekanand

    Co-Founder and Director

    Expert in data visualization and marketing econometrics with 10+ years

    Qualified Tableau trainer passionate about teaching business analytics

    Know More
    Wilson Consulting Private Limited Logo
  • Denver Dias - Faculty Director

    Denver Dias

    Senior Data Science Consultant

    Holds 8+ yrs exp. & delivered AI solutions for Fortune 500 firms

    Expert in A/B testing, ML models, and predictive analytics

    Know More
    S P Jain School of Global Management Logo
  • Mr. Udit Mehrotra - Faculty Director

    Mr. Udit Mehrotra

    Data Scientist, Stripe

    10+ years of experience in data science

    Former Data Scientist at Mc.Kinsey & Company, Dell

    Know More
    Stripe Logo

Watch inspiring success stories

  • learner image
    Watch story

    "The SQL and Python course enhanced my ability to extract practical insights from data"

    The program offered practical exercises in data analysis and programming. Professors were highly skilled, and the focus on SQL and Python greatly improved my technical abilities.

    Ashenafi Terefe

    Medical Technologist , USF

  • learner image
    Watch story

    "Hands-on projects and 1:1 sessions helped me build confidence in SQL, Python, and data visualization"

    The program offered a solid foundation in SQL, Python, and data visualization. The hands-on projects were highly effective in reinforcing learning, and the 1:1 sessions ensured I had the support I needed.

    Alexa Martin

    Senior HR DOT Compliance Analyst , DHL

Get dedicated career support

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    1:1 career sessions

    Interact personally with industry professionals to get valuable insights and guidance

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    Interview preparation

    Get an insiders perspective to understand what recruiters are looking for

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    Resume & Profile review

    Get your resume and LinkedIn profile reviewed by our experts to highlight your skills & projects

  • banner-image

    E-portfolio

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

Course fees

The program fee is 2,900 USD

Data Analytics Essentials Program: USD 2000

PL-300 Certification Training Program*: USD 900

Invest in your career

  • benifits-icon

    Understand data analytics from business, technical, and conceptual aspects

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    Analyze and visualize data using Excel, SQL, Python, and Tableau

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    Query and manage databases using SQL to generate insights and reports

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    Solve business problems with data storytelling and end-to-end Python analytics

*Great Learning delivers the PL-300 certification training program in collaboration with Microsoft. The University of Texas at Austin is not Involved in the program’s design or delivery

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Easy payment plans

Avail our flexible payment options & get financial assistance

  • INSTALLMENT PLANS

    Upto 3 months Installment plans

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Take the next step

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Apply to the program now or schedule a call with a program advisor

Unlock exclusive course sneak peek

Application Closes: 19th Jun 2025

Application Closes: 19th Jun 2025

Talk to our advisor for offers & course details

Admission Process

Admissions close once the required number of participants enroll. Apply early to secure your spot

  • steps icon

    1. Fill application form

    Apply by filling a simple online application form.

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    2. Interview Process

    A panel from Great Learning will review your application to determine your fit for the program.

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    3. Join program

    After a final review, you will receive an offer for a seat in the upcoming cohort of the program.

Batch start date

  • Online · 12th Jul 2025

    Admission closing soon

Frequently asked questions

Program Details
Admissions & Eligibility
Fee Related Queries

How will I be assessed during the Data Analytics course online?

The Data Analytics Essentials program is extensive, and learners are continually evaluated through quizzes, assignments, and projects.

What tools and techniques will the PL-300 Microsoft Power BI certification course cover?

This add-on Data analyst certification online program covers topics such as Power BI Desktop, Power Query, Data Modeling, Visualizations, DAX functions, and more. Additionally, learners will be exposed to best practices in Power BI Data Analytics, further preparing them for the PL-300 Microsoft Power BI Data Analyst exam.

Does the PL-300 Microsoft Power BI Data Analyst course include practice examinations?

Yes, the program features practice exams that mirror the PL-300 Microsoft Power BI certification test.

Why should I choose this Data Analytics course for beginners from the McCombs School of Business at The University of Texas at Austin?

The McCombs School of Business at the University of Texas at Austin is a well-respected business school in the USA. It is known for its comprehensive programs in areas such as entrepreneurship, finance, and accounting. With a proven track record of success, along with cutting-edge research and innovative teaching methods, you can be confident that you are learning from some of the best in the field.

How can I become a Microsoft Certified Power BI Data Analyst Associate?

You will have the option to enroll in an add-on Microsoft Power BI Data Analytics program alongside the Data Analytics Essentials program. 

Upon successfully completing the Microsoft Power BI Certification Program and passing the PL-300 exam, learners will earn the Microsoft Power BI Data Analyst certification.

Is this program a data analytics certification?

No. This Data Analytics Essentials program is a data analytics certificate program and not a certification. Upon completing the program, participants receive a certificate of completion in Data Analytics Essentials from the McCombs School of Business at The University of Texas at Austin. Additionally, you will get an option to complete PL-300 Microsoft Power BI Data Analytics certification program, where you will get a certification.

Will the sessions be live or recorded?

Learners will participate in live and interactive sessions over the weekend. If they miss any sessions, they can watch the recorded versions later at their convenience. Along with the live mentorship sessions, recorded lectures from Texas McCombs faculty and industry experts will be uploaded to the Learning Management System (LMS) on a weekly basis.

Will I be awarded any data science certificate after completing the course?

Upon successfully completing the program, you will receive a certificate of completion in Data Analytics Essentials from the McCombs School of Business at The University of Texas at Austin.

Will I receive any career support after completing this program in data analytics?

Yes, when you choose this data analytics program, you will receive career support from Great Learning, a reputed ed-tech platform for higher education and professional development. 


The career support services you will receive are as follows: 


Career Sessions: You will engage with industry experts and get dedicated career assistance. 

Resume and LinkedIn Profile Review: This program will assist you in creating a top-notch resume that highlights your skills and prior work experience. 

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

What job opportunities will become available after passing the Microsoft PL-300 Exam and obtaining the Certification?

By successfully completing the Microsoft PL-300 course and obtaining certification, learners will enhance their professional profiles, readying them for positions such as Data Analyst, Power BI Developer, Business Intelligence Analyst, and beyond.

What is the Data Analytics Essentials course from the McCombs School of Business at the University of Texas at Austin?

The Data Analytics Essentials program from the McCombs School of Business at the University of Texas at Austin is a 16-week online program designed to develop the critical analytics foundational skills you need to enter the world of data. This is among the best data science programs for beginners, designed by award-winning UT Austin faculty. These are some of the program highlights:


  • Duration: 16 weeks

  • Format: Online

  • Hands-on projects: Yes

  • Dedicated Program Manager: Yes

  • Career Support: Yes

  • Academic Learning Support: Yes (GL Community, Project Discussion Forums, Peer Groups)

  • Certificate: Yes. On successful completion, you will earn a Certificate of Completion from UT Austin

  • Continuing Education Units:  Yes. Earn 5.0 Continuing Education Units (CEUs) on successful completion of the program.

What is the duration of this UT Austin Data Analytics certificate course?

The program duration is 16 weeks, and it includes hands-on projects on real-world business problems. The program curriculum is designed by the McCombs School of Business faculty. Industry leaders take the live online masterclasses over the weekend.

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

We believe learning should be continuous; therefore, all lectures and learning materials will be available to students for three years after they complete the Data Analytics Essentials program.

What career opportunities will I receive after completing this Data Analytics program by Texas McCombs?

Upon successful completion of this program, you can pursue a broad range of career opportunities. Some of the most in-demand entry-level jobs in Data Analytics include the following:


  • Data Analyst

  • Business Analyst

  • BI Analyst

  • Data Journalist

  • Research Analyst

  • Product Analyst

  • Analytics Engineer

  • Data Architect

  • Data Engineer

What role does Great Learning play in this data analytics course for beginners?

The Data Analytics Essentials program is developed by Texas McCombs in partnership with Great Learning, a leading ed-tech platform for higher education and professional development.


Great Learning offers the following career support services to the learners of this program:


Career Sessions: Learners will interact directly with industry experts to gain career insights.


Resume and LinkedIn Profile Review: The program will help learners put together an outstanding resume that highlights their abilities and previous employment experience.


Interview Preparation: Learners can gain an insider's perspective on what hiring managers are looking for and learn how to ace interviews with the help of interview preparation sessions.


E-Portfolio: Learners will discover how to build an industry-ready portfolio to showcase their proficiency with languages, tools, and skills.


Learners will also get personalized assistance with a dedicated program manager from Great Learning to guide them for all their queries. 

What exactly does mentored learning involve?

Mentored sessions are the live online mentorship sessions over the weekend, designed for dynamic two-way voice and video communication. In these engaging sessions, you will be part of a focused micro-class consisting of 20-25 learners, ensuring personalized attention and a collaborative learning environment.

Who would be the faculty teaching this Data Analytics beginners’ course?

The program will be taught by world-renowned faculty from Texas McCombs. Leading industry experts will conduct the industry sessions. The curriculum has been designed by UT Austin faculty to help you understand the fundamentals of data analytics.

What tools are covered in this data science course for beginners?

You will get familiar with several in-demand skills and tools in this program, including:


  • Excel

  • Python

  • RDBMS

  • Querying Data with SQL

  • NumPy

  • Pandas

  • Data Visualization using Tableau

What is the Data Analytics program syllabus for beginners?

The program syllabus has been developed to fulfill the requirements for an entry-level data science job. This curriculum will discuss the following topics to help learners pursue fruitful careers in Data Analytics:


Pre-Work Module: Introduction to Excel, Descriptive Statistics


Data Analytics Foundations: Overview of the World of Data and Generating Insights using Excel.


Data Analytics with SQL: Querying Data with SQL and Advanced Querying to extract business insights.


Data-driven Insights using Python: Data Transformation using Numpy and Pandas, Data Visualization with Seaborn, and Exploratory Data Analysis.


Self-Paced Modules: Creative Storytelling with Tableau, Building Interactive Dashboards using Tableau, ChatGPT and its applications. 


PL-300- Microsoft Power BI Data Analytics certification Training Program for the preparation of the Microsoft Power BI Data Analyst PL-300 certification exam.

What is unique about this Data Analytics beginners course?

The Data Analysis beginners' program is unique in the following aspects: 


Learners will learn from professional data analysts with a variety of backgrounds, weekly one-on-one mentoring sessions, and frequent real-world case studies and hands-on projects. 


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


Learners will develop analytical skills through the comprehensive curriculum.

What are the benefits of enrolling in this Data Analytics program from the McCombs School of Business at the University of Texas at Austin?

The benefits of enrolling in this world-class and best Data Analytics course for beginners include the following:


The McCombs School Advantage: The McCombs School of Business at the University of Texas at Austin is a reputable business school at a renowned public research university. Learners can rest assured that they are learning from the best of the best.


Industry-relevant Curriculum: Several highly qualified faculty members from the McCombs School developed the curriculum for this program. This comprehensive curriculum covers industry-relevant subjects, such as Excel, Python Programming, Descriptive Statistics, Data Analytics Foundations, SQL, Numpy, Pandas, Exploratory Data Analysis (EDA), Generative AI and Data Visualization with Tableau.


 

Interactive Sessions: Through live interactive micro-classes, learners can connect with mentors and peers. 



Hands-on Learning: With hands-on learning, learners will gain in-depth knowledge of various critical concepts and discover how to apply them in the real world.



Prominent Faculty and Industry Experts: In order to give learners a practical understanding of essential concepts, the program brings together the distinguished faculty of The McCombs School and a global team of highly skilled Data Analysts and Business Analysts.



Industry-relevant Projects: Learners will work on hands-on projects spread across various modules. They will implement these projects alongside established data experts and fellow learners worldwide.


 

Live Online Mentoring Sessions: During these sessions, learners can speak with mentors from various fields. Additionally, they will gain assistance with projects and other critical concepts through live mentoring sessions.



Great Learning Advantage: Learners will gain access to dedicated career support from Great Learning throughout their educational journey, including career guidance sessions, resume reviews, LinkedIn Profile reviews, interview preparation, and e-portfolios.

 


Become Job-ready: This data analyst course for beginners will equip learners with theoretical knowledge and practical skills through case studies and hands-on projects. They will enhance their resume and secure career opportunities with Great Learning’s career support program. They’ll also get the opportunity to network with well-established industry experts, increasing their chances of succeeding in the Data Analytics field.

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

The McCombs School of Business at the University of Texas at Austin is ranked 


#6 in MS - Business Analytics (QS World University rankings, 2024) 

#4 in Master’s in Business Analytics (QS World University Rankings, 2023) 

#6 in Executive Education Custom Programs (Financial Times, 2022) 

#1 in U.S., Big Data Management in MS Business Analytics (Eduniversal, 2024)

Who is the Data Analysis for Beginners course best suited for?

This is among the best data science courses for beginners and is best suited for: 


Recent graduates and early career professionals looking to acquire job-ready skills in business intelligence and data analytics domains. The program trains and prepares students for job roles like business analyst or data analyst. 


Candidates 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 short timeframe with a realistic resource investment.

Who can apply for this Microsoft Power BI Certification Program?

Learners in the Data Analytics program seeking career advancement and Microsoft Power BI certification can enroll. It focuses on Power BI and welcomes anyone interested in Power BI Data Analytics.

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 cohort. The seats available for this program are subject to the first-come, first-served rule. Apply early to secure your seats.

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

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


1. Fill application form

Apply by filling a simple online application form.


2. Interview Process

A panel from Great Learning will review your application to determine your fit for the program.


3. Join the program

After a final review, you will receive an offer for a seat in the upcoming cohort of the program.



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

Does this course have a refund/cancellation policy?

Submitting the admission fee confirms your enrollment in the program, and the following cancellation policies apply:


Within 48 Hours of Enrollment: Full refund.


After 48 Hours: Admission fee is non-refundable.


Fee Paid Beyond the Admission Fee:


>4 Weeks Before Start Date: Full refund.


>2 Weeks Before Start Date: 75% refund.


>24 Hours Before Start Date: 50% refund.


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


Cancellation must be requested in writing to the program office.

Are books or online learning resources subject to additional fees?

All learning materials will be accessible through the Learning Management System (LMS). Please note that there will be no additional fees associated with books or other learning resources.

What is the data analytics course fee?

The fee to pursue this program is USD 2900*. 


Data Analytics Essentials Program: USD 2000 


PL-300 certification Training program (Power BI certification cost): USD 900 *Great Learning delivers the PL-300 certification training program in collaboration with Microsoft. The University of Texas at Austin is not Involved in the program’s design or delivery 


[Contact our admissions office at +1 512 877 8310 for more details on fees, payment plans and upcoming cohort]

Got more questions? Talk to us

Connect with a program advisor and get your queries resolved

Speak with our expert +1 512 877 8310 or email to dae.utaustin@mygreatlearning.com

career guidance

Delivered in Collaboration with:

McCombs School of Business at The University of Texas at Austin is collaborating with Great Learning to deliver certificate program in Data Analytics Essentials. Great Learning is an ed-tech company that has empowered learners from over 170+ countries in achieving positive outcomes for their career growth.

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