Post-Graduate Program in Data Science & Business Analytics

• Personalised mentored learning in small groups of up to 15 learners
• Covers industry-relevant topics in depth, with hands-on applications and case studies
• Provides hands-on exposure to tools such as Python, Tableau and Advanced Excel. Datasets are also provided
• Experiential learning projects at the end of every module enable candidates to apply their learning to real-world business problems
• Interactive live sessions with industry experts and mentors provide current industry knowledge and insights
• The online delivery model makes it convenient for working professionals to pace their learning and get doubts cleared without having to quit their jobs or travel anywhere

The PGP-DSBA curriculum has been designed in collaboration with UT Austin. The teaching and content in the program is by faculty from UT Austin, Great Learning and other practicing data scientists and analytics experts. The capstone projects are approved by UT Austin Faculty.

Upon successful completion, participants earn a certificate of completion from The University of Texas at Austin.
 

Participants are guided through a unique mentored learning process that happens in a micro-class of 20-22 learners, and guided by a senior industry mentor. These are live sessions with two-way audio and video interaction and take place on weekends.

The primary objective of the program is to help you prepare for a career in the domain. Understanding the importance of gaining credibility, knowledge, and a body of work in landing you a job, we have worked backwards to design a program that helps you stand out on all 4 fronts. 

• The certificate from UT Austin serves to give you credibility and recognition in the global industry.
• Best-in-class recorded content from UT Austin faculty and hands-on practical training equip you with the knowledge to succeed.
• The projects you complete add on to your body of work to prepare an industry-ready portfolio by the end of the program.
• Interacting with established practitioners and other aspiring data science professionals helps you build your network.

In addition, the program provides career guidance sessions with industry practitioners and mentoring/support on the softer aspects of job hunting such as resume review, LinkedIn profile review, interview preparation, etc.

Yes. The program is covered using recorded content delivered by academic and industry faculty and live instructor-led online micro-classes which happens in a group of 20-22 learners. All assessments will also be conducted online.

Candidates can access all the necessary learning material online through the Learning Management System.

Participants do several experiential projects on Time series forecasting, Predictive modeling, Advanced statistics, Estimation & Hypothesis testing, and Data mining, which requires candidates to use and apply the concepts learned across all the different modules in these projects.

• Python
• Tableau

The McCombs School of Business at the University of Texas at Austin is ranked No. 6 in the world by QS Business Analytics Ranking, 2021.

The projects include real-world projects and case studies. You'll work on data analysis, predictive modelling, machine learning, and more, utilizing tools like Python, R, and Tableau, providing a practical understanding of the concepts.

Yes. This program is often considered one of the best Business Analyst courses for those looking to change or advance their careers. Its comprehensive curriculum, industry-aligned projects, and connection with top-tier faculty make it suitable for those new to the field or seeking to upgrade their existing skills.

Graduates of this course can explore career opportunities in various domains such as finance, healthcare, retail, technology, and more. Typical roles include Data Analyst, Business Analyst, Data Scientist, and Business Intelligence Specialist. The program's strong reputation and industry connections significantly enhance job prospects.

Yes. Participants will have the opportunity to interact with UT Austin faculty. Regular classes, Q&A sessions, and one-on-one mentorship opportunities ensure an engaging learning experience.

The business analyst course combines online sessions, tutorials, hands-on projects, mentorship from industry experts, and career support. This blended approach ensures both theoretical understanding and practical application of data science and business analytics skills. In addition, there is an optional 6-week module that covers Microsoft Power BI, where learners can master the tool for data analysis.

A business analyst course is a structured educational program designed to teach individuals the skills, knowledge, and techniques required to become effective business analysts. These courses focus on various aspects of business analysis, including requirements gathering, process modelling, data analysis, and communication with stakeholders. Participants learn how to identify business needs, analyze and interpret data, and propose solutions to improve the efficiency and effectiveness of business operations.
 

The Business Analyst course curriculum typically covers topics such as:
 

• Introduction to business analysis: This includes understanding the role and responsibilities of a business analyst, as well as the importance of business analysis in organizations.
   

• Requirements elicitation and management: Participants learn various techniques for gathering, documenting, and validating business requirements from stakeholders.
   

• Business process modelling: This involves the use of diagrams and flowcharts to represent and analyze business processes, identifying areas for improvement.
   

• Data analysis and interpretation: Students learn to analyze and interpret data using tools and techniques such as spreadsheets, databases, and data visualization software.
   

• Solution evaluation and validation: This includes assessing the feasibility and effectiveness of proposed solutions, as well as validating them against the original requirements.
   

• Communication and stakeholder management: Participants develop the ability to effectively communicate with various stakeholders, including managers, team members, and clients.
   

• Tools and techniques: Students are exposed to different business analysis tools and methodologies, such as SWOT analysis, PESTLE analysis, and Agile methodologies.
   

Business analyst courses can be found in various formats, such as online or in-person classes, part-time or full-time programs, and short-term workshops or long-term certification courses. 

Each week involves around 2-3 hours of recorded lectures and an additional 2-hour mentored learning session each weekend, which includes hands-on practical applications and problem-solving. The program also involves around an hour of practice exercises or assessments each week. Additionally, based on your background, you should expect to invest 2 to 4 hours every week in self-study and practice. So, that amounts to a time commitment of 8-10 hours per week.

The Post Graduate Program in Data Science and Business Analytics is an online professional certificate program offered by the McCombs School of Business in collaboration with Great Learning. You will receive the grade sheet post-completion; however, the program does not carry any credits. Also, your performance will be assessed through individual assessments and module completion to determine your eligibility for the certificate.

Upon completing all the modules in accordance with the qualifying requirements for the program, you'll receive a certificate from the University of Texas at Austin.

PGP-DSBA is mostly pursued by working professionals planning to make a career transition into analytics roles. We also have students in their final year of graduation benefiting from the program. Graduation in a quantitative discipline like engineering, mathematics, sciences, statistics, economics, etc, would help participants get the most out of PGP-DSBA program.

Data has become highly influential. Data is the future. The domain of Data Science is already observed to create wonders for most of the industries it is being applied to. Data Scientists are creating a significant impact and are causing a great revolution.

The scope of Data Science is far-reaching. The demand and need for data scientists are increasing exponentially as days pass by. This demand is rising at a rapid pace and is expected to grow even more in the future. Hence many professionals are seeking a career transition into the field of Data Science.

Business Analytics is another exciting technological domain that has gained utmost popularity in recent times. Business Analytics and Data Science are employed together for the best outcomes. 

The technologies of Data Science And Business Analytics are also believed to take over most of the existing job roles. Hence to build a secured career taking up a data science and business analytics course has become a reliable choice. The applications of data science are delivering the most accurate and reliable results. Data Science and business analytics are also applied in solving most complex business problems. 

The applications of Data Science are already being applied to many fields such as gaming, robotics, healthcare, marketing, finance, and more. Data Science and Business Analytics are assumed to extend their territories to several other fields and build new dynamics. 

These domains also offer one of the highest-paid job roles across the globe. Hence, choose the best data science and Business analytics certificate courses to fit into the best job roles of the 21st century.

The job opportunities in this field are captivating, attracting both young professionals and career changers to pursue a career as Data Scientists or Business Analysts. Online courses in Data Science and Business Analytics have become popular among those seeking to upskill and enter this rapidly growing industry.

Let us look into a few of the major job positions of Data Science and Business Analytics.

1. Data Analyst

2. Data Architect

3. Statistician

4. Business Analyst

5. Database Administrator

6. Data Engineer

7. Data Scientist

Pursuing a data science and analytics course would aid you get into one of the above-mentioned job roles.

Many believe that Data Science and Business Analytics are the same. Many also use these terms interchangeably. Below are a few differences between Data Science and Business Analytics. These two domains when combined together perform wonders. Hence many are desiring to pursue a Data Science and Business Analytics online course.

• Data Science is the fundamental application of various machine learning methods and ideas to derive significant insights from raw data while Business analytics deals with the collection of data and evaluates the collected data towards accomplishing the business goals.
• Data Science focuses on problem-solving whereas Business Analytics focuses on decision making.
• Data Scientists strives to find the reason for driving those trends and Business Analysts aims to discover the trends of the data
• Data Science applies a lot of coding practices while Business Analytics does not demand programming skills.
• Data Science implements algorithms, statistics to derive insights from data and Business analytics employs the statistical analysis of structured data.
• The ultimate agenda of Data Science is to pose questions and understand the analyzed collected data whereas Business Analytics renders reliable solutions to specific business problems.

Learn more about these technologies by taking up a data Science and business analyst course online.

Data analytics is another interesting domain that is driving interest in many to pursue data analytics courses. Data Science and Data Analytics are two different terms as well as domains that are often referred to as one. Nevertheless, there exists a lot of differences between these two terms. If you are keen about pursuing a data analytics course, it is crucial to learn the differences between Data Science and Data Analytics.

Below are the differences between Data Science and Data Analytics.

• Data Science is the integral application of several machine learning techniques and concepts to extract meaningful insights from raw data and Data Analytics refers to the analysis and classification of the patterns of the information collected to derive the best conclusions that aids in meeting business goals.
• Data science detects patterns in the existing data while Data Analytics is used to sort data to fulfill the organizational needs.
• Data Science has a macro-level scope. However, the scope of Data Analytics is micro.
• The ultimate agenda of Data Science is to ask questions whereas Data Analytics aims to find the perfect and actionable data.
• Data Science focuses on problem-solving while Data Analytics concentrates on decision making
• Data Science exercises Mathematics, Statistics, and Programming Skills. But, Data Analytics applies qualitative and quantitative techniques.
• Data science is implemented in technological domains such as Artificial Intelligence, Machine Learning, and many more while Data analytics is applied in e-commerce, gaming, and other sectors to resolve the issues associated with data.
• Data Science predicts the future whereas Data Analytics provides a day-to-day analysis of the data.

The domain of Data Science is applied in many industries.The applications of Data Science and Business Analytics  are not limited to the IT sector. Hence, many are seeking the best business analytics courses online to get into the most exciting job roles. We all are witnessing the hand of data science which we never knew.

Below are a few of the applications of Data Science and Business Analytics offered to different domains

1. Internet Search

Data Science and Business Analytics  plays a vital role in displaying the most accurate results for internet search queries. Data Science is an integral technology used by most search engines such as google, bing, opera, and more.

2.Speech Recognition

One of the applications of Data Science is speech recognition. Data Science and Business Analytics are employed to understand the voice notes and produce accurate outcomes. Siri, Alexa, Google voice assistant, and more are a few examples that exercise data science to regulate speech recognition services. 

3. Targeted Advertising

Data Science promotes target advertising. Data science algorithms are rapidly employed in digital marketing to identify the target audience and advertise accordingly. Data Science and Business Analytics plays a major role in increasing the CTR( call through rate). These targets are made by studying the user's past behavior patterns.

4. Recommendations

Data Science is employed to make the best recommendations of the products and services of the e commerce websites. Amazon, Flipkart, Spotify, Netflix, and more employ data science to show the best recommendations to its users. This enhances the user's experience as they encounter a personalized shopping experience.

Out of the many, below are a few attributes of Data Science that make it the best technological domain to work for.

1. Data Science and Business Analytics are high in demand

Data Science and Business Analytics are the two domains which have got a great demand. Even as many industries are adapting Data Science and Business Analytics at a rapid pace, there is a significant rise in demand for these technologies.

2. Offers highest-paid career roles

The job roles offered in these domains are considered highly prestigious. These job roles are also observed to be one of the highest-paid ones across the country and abroad.

3. A huge scope

Data Science and Business Analytics are technologies that are not limited to the IT sector. Data Science and Business Analytics have been embraced by most industries such as Healthcare, Gaming, Social Media, Digital Marketing, Agriculture, and many more.

4. The most secure domains.

Even as we live in a world where technological upgrades happen every single day, Data Science and Business Analytics offers secured job roles. Data Science and Business Analytics are expected to take over many of the existing job roles. Hence it is crucial to consider a career that stands tall and secured. Data Science and Business Analytics are surely the domains that offer the most secured job roles.

There are a lot of industries that are already employing Data Science and Business Analytics for the unbelievable benefits they offer. The list of the industries/ domains adapting Data Science and Business Analytics is increasing rapidly. Considering this, the demand for Data Science and Business Analyst online courses is increasing day by day as many are aspiring to get into these job roles.

Business

Data Science and Business Analytics are employed to derive the best business solutions and solve complex business problems. Data Science and Business Analytics are rapidly being applied in businesses as they are observed to serve great benefits such as predict the most accurate outcomes, assessing business decisions, formulating effective business strategies, leveraging the data, and more.

Agriculture

Data Science and Business Analytics are assisting the farmers by offering them many benefits such as weather prediction, analyzing the soil, pest control, disease detection, recommendation of the best fertilizers, and more.

Gaming Industry

Data Science and Business Analytics are applied in designing games. These technologies are helping the designers in designing the games that keep the user engaged and enthusiastic. The data science algorithms study the user's moves and give a tough competition which makes the game more exciting.

Robotics

Data Science and Business Analytics are employed in designing robots. The tools and techniques of Data Science and Business Analytics are applied to create the most intelligent robots. As Data Science is used in Artificial Intelligence and Machine Learning, it stands in the gap to design many technological innovations.

Apart from the above-mentioned industries, these technologies are also used in many other industries such as E commerce, the financial sector, education, and more.

A data analytics course helps students gather, process, analyze, and understand data to gain insights to help them make better decisions. This course covers various aspects of data analytics, such as predictive modelling, statistical analysis, and data visualization. Data analytics courses commonly cover the following subjects:
 

• Data cleaning, managing missing data, and data transformation methods are all part of data exploration and preprocessing.

• Basics of probability distributions, hypothesis testing, and descriptive and inferential statistics comprise statistical analysis.

• Data representation in graphs, charts, and other visual forms.

• Introduction to supervised and unsupervised learning methods, model assessment, and model optimization in machine learning.
   

Data analytics courses are offered in various forms, such as online or in-person classes, part-time or full-time programs, and short-term workshops or longer certification courses. Upon completion, participants can apply these skills across various industries, such as marketing, finance, healthcare, and more.

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.