PG DIPLOMA IN DATA SCIENCE

Program Overview

The PG Diploma in Data Science offered in collaboration with UPES University is a career-focused, advanced-level data science program designed for graduates aiming to build successful careers in data analytics, machine learning, artificial intelligence, and business intelligence. Recognized as one of the best PG diploma data science courses in Kerala, this program emphasizes practical skill development, real-world project exposure, and industry-recognized certifications aligned with current market demands.

With comprehensive training in Python, SQL, machine learning, deep learning, data visualization, NLP, and Power BI, this PG diploma equips learners with the technical expertise and analytical mindset required by IT companies, analytics firms, startups, and multinational organizations.

Course Overview

The PG Diploma in Data Science (UPES) offers a perfect blend of theory and hands-on practice. Students work on live projects, complete a 3-month internship, and receive a 3-month experience certificate, ensuring strong industry exposure. The program focuses on transforming raw data into meaningful insights to support data-driven decision-making.

Additional Certifications & Professional Trainings

Main certications

• UPES PGCP

•  ABE- PG DIPLOMA

  
  

Students enrolled in this program receive valuable add-on certifications and practical exposure, including:

1. SECP – Level 1 Certificate

2. SECP – Level 2 Certificate

3. MS Office with AI

4. 3-Month Internship

5. 3-Month Experience Certificate

6. Live Project

7. Spoken English Training

These components make this program one of the most job-oriented PG diploma data science courses in Kerala.

Syllabus Overview (Short Explanation)

1. Python

   • Programming fundamentals, data structures, and scripting for data analysis

2. SQL

   • Database concepts, data querying, and data management techniques

3. Pandas and Data Visualization

   • Data cleaning, manipulation, and visual representation of insights

4. Statistics and Maths

   • Statistical methods, probability, and mathematical foundations for analytics

5. Machine Learning and Deep Learning

   • Predictive modeling, supervised and unsupervised learning, and neural networks

6. NLP and Power BI

   • Natural Language Processing techniques and business intelligence reporting using Power BI