Diploma in Data Analytics
Program Overview
The Diploma in Data Analytics is designed to equip students with the essential knowledge and practical skills required to collect, process, analyze, interpret, and visualize data. In today's data-driven environment, organizations across industries rely on data analytics to make informed decisions, identify trends, improve performance, and solve complex business problems. This program provides learners with a strong foundation in modern data analysis techniques and industry-relevant analytical tools.
The curriculum covers important areas such as Introduction to Data Analytics, Statistical Analysis, Data Analytics using Excel, Programming in Python, Machine Learning, Data Analytics using R, Data Visualization, NumPy, and Pandas. Students learn how to work with datasets, perform statistical analysis, organize and manipulate data, create visual reports, and use programming languages and analytical tools to extract meaningful insights.
The program emphasizes practical learning and analytical problem-solving. Through hands-on training in Excel, Python, R, NumPy, Pandas, and data visualization techniques, learners can develop the ability to analyze structured data and present insights effectively. The introduction to machine learning also helps students understand how data-driven models can be used for prediction and intelligent decision-making.
After completing the program, learners can explore opportunities and further education in areas such as data analytics, business analytics, data visualization, data management, Python programming, statistical analysis, and machine learning. The diploma provides a valuable foundation for students and professionals seeking to develop analytical skills for careers in the growing data and technology sectors.
Eligibility Criteria
The candidate must have graduated from 12th standard.
Approval Details
MHRD, Government of India and UGC
Curriculum
- Introduction to Data Analytics
- Introduction to Statistical Analysis
- Data Analytics using Excel
- Programming in Python
- Machine Learning
- Data Analytics using R
- Data Visualization
- Numpy and Pandas
Fee Structure
Admission Process
Students can apply for theย Diploma Data Analyticsย programme through EasyShiksha. The complete application process is designed to make admission simple and convenient for eligible students.
Step 1: Click on Apply Now
Click theย Apply Nowย button on theย Diploma Data Analyticsย programme page and begin your application through EasyShiksha.
Step 2: Complete Personal Information
Fill in the required personal, contact and academic details accurately in the application form.
Step 3: Upload Required Documents
Upload the required documents for eligibility and admission verification as specified during the application process.
Step 4: Pay Application Fee
Pay the applicableย application feeย through the available online payment options to submit your application and initiate the admission process.
Step 5: Application Review
Theย EasyShiksha team reviews your application and submitted documentsย to verify your eligibility and ensure that the required information and documents have been provided.
Step 6: University Enrollment
Once the application is successfully reviewed and the student is found eligible, EasyShiksha facilitates theย enrollment process withย Kurukshetra University.
Step 7: LMS Access
After successful enrollment, the student is provided access to theย Learning Management System (LMS)ย to begin their academic journey and access the available learning resources.
Start Your Application
Ready to begin your journey in Software Development? Clickย Apply Nowย to submit your application through EasyShiksha.
Kurukshetra University, Kurukshetra
Kurukshetra University is a UGC-recognized private university located in Kurukshetra, Haryana, India. Known for its strong industry connections, cutting-edge curriculum, and commitment to technology-driven education, Kurukshetra University has established itself as one of central India's premier higher education institutions.
The university's vision is to foster academic excellence, industry readiness, and global competitiveness among its graduates โ making it an ideal partner for EasyShiksha's mission of accessible, quality online education.
EasyShiksha has signed an MoU with Kurukshetra University to facilitate applications for various university programs and jointly offer B.Voc programs. All degrees and certifications under these programs will be awarded by Kurukshetra University. The EasyShiksha team will provide complete assistance and support throughout the admission and program process.
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Frequently Asked Questions
Yes. Kurukshetra University offers programmes through its Directorate of Distance Education (DDE), including programmes under Open and Distance Learning (ODL) and Online Learning (OL).
The Directorate of Distance Education (DDE) is the university's dedicated unit for delivering higher education through distance and online learning modes.
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Recognition of an online or distance programme is programme- and admission-session-specific. Students should verify the current KUK programme's recognition/entitlement on the official UGC-DEB portal before admission.
UGC regulations provide that recognized ODL/Online undergraduate and postgraduate degrees are treated as equivalent to corresponding conventional-mode degrees, subject to the applicable UGC requirements.
The Diploma in Data Analytics is a skill-focused program that teaches students how to collect, process, analyze, interpret, and visualize data using modern analytical tools and techniques.
The program covers Introduction to Data Analytics, Statistical Analysis, Data Analytics using Excel, Programming in Python, Machine Learning, Data Analytics using R, Data Visualization, NumPy, and Pandas.
Yes. The program includes Data Analytics using Excel, helping students develop practical skills for organizing, analyzing, and interpreting data.
Yes. Students learn Programming in Python and use Python-based tools such as NumPy and Pandas for data analysis and manipulation.
NumPy and Pandas are widely used Python libraries that help users work with numerical data, datasets, data manipulation, analysis, and processing tasks.










