Data Science & Analytics -
Powered By IBM

Data Science & Analytics -
Powered By IBM

The MCA Data Science course at ADYPU will equip you with the skills and knowledge to become a proficient data scientist. Throughout the program, you will have the opportunity to apply your knowledge to solve real-world problems through hands-on labs, workshops, case studies, and a capstone project.

Data Science & Analytics – Powered By IBM

Duration: Two Years | Full Time

Eligibility: Passed B.C.A/ B.Sc. (Computer Science)/ B.Sc. (IT) / B.E. (CSE)/ B.Tech. (CSE) / B.E. (IT) / B.Tech. (IT) or equivalent Degree. OR Passed any graduation degree (e.g.: B.E. / B.Tech. / B.Sc / B.Com. / B.A./ B. Voc./ etc.,) preferably with Mathematics at 10+2 level or at Graduation level Obtained at least 50% marks (45% marks in case of candidates belonging to reserved category) in the qualifying examination.

Core
Curriculum

1. Foundational Courses:
– Mathematical Foundations: Linear algebra, calculus, probability.
– Statistical Methods: Descriptive and inferential statistics.
– Programming Fundamentals: Introduction to Python and/or R.
2. Data Science Essentials:
– Data Cleaning and Preprocessing.
– Exploratory Data Analysis (EDA).
– Database Management Systems.
3. Machine Learning:
– Supervised Learning: Regression, classification.
– Unsupervised Learning: Clustering, dimensionality reduction.
– Ensemble Learning, Neural Networks.
4. Big Data Technologies:
– Understanding big data concepts.
– Hands-on experience with Hadoop and Spark.
5. Data Visualization:
– Creating visualizations with tools like Tableau and matplotlib.
– Communicating insights effectively.
6. Natural Language Processing (NLP):
– Text processing, sentiment analysis, and applications of NLP.
7. Capstone Project:
– Applying knowledge to solve a real-world problem in collaboration with industry partners.

What will you explore as part of the program?

1. Mathematical Foundations:
2. Computer Science Fundamentals:
3. Data Cleaning and Preprocessing:
4. Exploratory Data Analysis (EDA):
5. Machine Learning:
6. Big Data Technologies:
7. Natural Language Processing (NLP):
8. Deep Learning:
9. Data Visualization and Communication:

1. Ajeenkya Genius Scholarship

2. ADYP Group Progression

3. Pune Pride Scholarship

4. ADYPU Divyang Excellence Scholarship

5. Khelo India Sports Delight Scholarship

6. My India Pride Scholarship

7. ADYPU Resilience Scholarship

8. ADYPU/ADYPG Employee Family Kids

9. Beti Padhao Scholarship

10. ADYPU Sibling Scholarship

11. ADYPU Entrance Talent Hunt Scholarship


How will you be taught?

1. Lectures
– Theoretical concepts delivered through lectures by experienced faculty.
2. Hands-on Labs:
– Practical sessions for coding and implementing data science techniques.
3. Workshops:
– Interactive sessions focusing on problem-solving and real-world applications.
4. Guest Lectures:
– Industry experts sharing insights and experiences.
5. Case Studies:
– Analyzing and discussing real-world data science case studies.
6. Internships
– 6 months of industry integration via immersive internships and projects.

How you will spend your time?

1. Classroom Learning:
– Attend lectures to grasp theoretical foundations.
2. Laboratory Sessions:
– Apply concepts through hands-on coding and experimentation.
3. Self-Study:
– Individual study to reinforce concepts and work on assignments.
4. Project Work:
– Collaborate on individual and group projects.
5. Networking:
– Engage with faculty, peers, and industry professionals.

Activities for this program

1. Industry Internships:
– Gain practical experience through internships in data science roles.
2. Hackathons and Competitions:
– Participate in coding competitions and hackathons to enhance problem-solving skills.
3. Seminars and Conferences:
– Attend events to stay updated on the latest trends and advancements in data science.
4. Professional Certifications:
– Opportunities to earn relevant certifications alongside the MCA degree.

Career & Opportunities

Career & Opportunities
1. Data Scientist
2. Machine Learning Engineer
3. Big Data Analyst
4. Data Engineer
5. Business Intelligence Analyst
6. Consultant
7. Researcher
8. Entrepreneur