Manipal Online University
Data Analytics
Manipal Online University
₹1.4L – ₹1.4L
Total Fees
3 Years
Duration
ONLINE
Mode
★ 4.0
Rating
Get Free Counseling
Talk to an expert about Data Analytics at Manipal Online University
- ✓ 100% Free Guidance
- ✓ Expert Counselors
- ✓ Reply within 24 hrs
About This Program at Manipal Online University
Other Programs at Manipal Online University
Course Curriculum
| Semester 1 | Semester 2 | Semester 3 | Semester 4 | Semester 5 | Semester 6 |
|---|---|---|---|---|---|
| Introduction to Computer Science – Basics of computer systems, software, hardware, and digital literacy. | Object-Oriented Programming – Concepts of classes, objects, inheritance, and polymorphism. | Data Structures and Algorithms – Efficient storage, retrieval, and processing of data. | Data Visualization and Reporting – Tools and techniques for representing data insights effectively (Tableau, Power BI). | Artificial Intelligence for Data Science – AI concepts, neural networks, and practical applications. | Capstone Project / Internship – Implementation of a comprehensive project using real-world data, analytics tools, and techniques. |
| Programming Fundamentals (Python / C++) – Introduction to programming concepts, data types, control structures, and problem-solving. | Database Management Systems (DBMS) – Data modeling, SQL, and relational database management. | Data Analytics Techniques – Descriptive analytics, exploratory data analysis, and business intelligence | Machine Learning Fundamentals – Supervised and unsupervised learning, model training, and evaluation. | Cloud Computing and Data Storage – Using cloud platforms for storage, computation, and scalable analytics solutions. | Data Ethics and Governance – Understanding ethical, legal, and privacy issues in data handling. |
| Mathematics for Computing – Sets, relations, functions, matrices, and fundamentals of discrete mathematics for programming. | Probability and Statistics – Basics of probability, descriptive statistics, and inferential analysis. | Python for Data Science – Using Python libraries such as Pandas, NumPy, and Matplotlib for data handling and visualization. | Big Data Analytics – Introduction to Hadoop, Spark, and processing large-scale datasets. | Business Analytics and Decision Making – Applying data analytics to solve business problems and support strategic decisions. | Advanced Machine Learning and AI Applications – Deep learning, reinforcement learning, and AI-based solutions. |
| Business Communication – Effective communication skills for professional settings. | Web Technologies – Fundamentals of HTML, CSS, JavaScript, and web application development. | Operating Systems and Networking – Concepts of OS, file systems, and networking basics. | Data Mining and Predictive Modeling – Techniques to identify patterns and forecast outcomes. | Capstone Project Preparation – Planning and designing projects based on real-world datasets. | Industry Integration and Professional Skills – Preparing for job roles through workshops, case studies, and resume-building exercises. |
| Environmental Studies – Principles of sustainability and the impact of technology on the environment. | Software Engineering Principles – Introduction to SDLC, software design, and project management. | Elective 1 – Choice of specialization or skill-based course in emerging technologies. | Elective 2 – Advanced topics or applied analytics modules. | Elective 3 – Advanced elective in data science, analytics, or programming. | Comprehensive Assessment / Viva – Final evaluation of technical knowledge, analytical skills, and project outcomes. |
Learning Outcomes
What you will achieve after completing this program
Graduates gain strong skills in programming languages such as Python, R, SQL, and Java, enabling them to efficiently manipulate data, develop algorithms, and create automated solutions. They are adept at handling both structured and unstructured datasets and can implement database management systems to store and retrieve information effectively.
Students develop a deep understanding of statistical methods, probability, and data analytics techniques. This empowers them to analyze trends, identify patterns, and make data-driven decisions that support business objectives. Their ability to apply quantitative methods ensures accuracy and reliability in deriving insights from complex datasets.
The program provides exposure to machine learning algorithms, predictive modeling, and AI-based solutions. Graduates can build models to forecast outcomes, recognize patterns, and automate processes, positioning them to contribute to innovation and efficiency in data-centric projects across industries.
A key learning outcome is the ability to translate complex analytical results into meaningful insights using visualization tools like Tableau, Power BI, and Python libraries. Graduates can communicate findings effectively to stakeholders, bridging the gap between technical analysis and business strategy.
Eligibility Criteria
Who Can Apply
Candidates must have completed 10+2 (Class 12 or equivalent) from a recognized board of education.
Students from any stream (Science, Commerce, or Arts) are eligible, though a background in mathematics is advantageous.
Required Documents
10th & 12th Marksheets
Graduation Certificate
Government ID Proof
Passport Size Photo
Finance Your Education
Total Program Fee
₹1.4L
≈ ₹23K per semester
Low Cost EMI
Contact admissions for EMI options
Scholarship
Ask counselor about scholarship eligibility
Placement & Careers
Career Opportunities
Job Roles
Top Recruiters
Fee Structure
| Total Program Fee | ₹1.4L – ₹1.4L |
| Semester Fee | ₹23K |
| Duration | 3 Years |
| Mode | ONLINE |
| Exam Fee | Included |
Questions & Answers
Questions & Answers
No questions yet
Be the first to ask a question.
Frequently Asked Questions
Data Analytics
Manipal Online University