PG Diploma in
Data Science
The program is the perfect blend of theoretical and practical classes that prepare student to be job-ready for the most demanding career of data science.
Our Advantage:
Credit Transfer
Internship and Placement
 NetworkingÂ
Industrial Project
Duration of Course
1 Year
Time Commitment
20 Hrs/ Week
Start Date
10 May, 2021
Mode
Blended Learning
Credit
Yes
Key Highlights
Doorway to International Master Degree Program
Student can transfer their credit to pursue Master program in some top-level universities we had tie-ups with. This program accounts for 40 to 45% of Master degree program.
No Prior Background in Computer or Data Science is required
Individual with Bachelor degree in Engineering, Management, and Science can apply for this program. The only pre-requisite is fundamentals of basic mathematics, statistics, and probability.Â
Advance Your Career
Gain relevant skills to up your game at work in a career-focused program.
Internship and Job Placement
Data Science is the most on-demand job with high salary. We connect our graduate with various companies worldwide for internship and job opportunities during and after completion of program.
About Program
The program is the perfect blend of theoretical and practical classes that prepare student to be job-ready for the most demanding career of data science. The one-year diploma course is designed for graduates (at least Bachelor degree) from management, engineering and science with foundational knowledge of basic mathematics, statistics, and probability. The student will learn Python Programming from scratch along with learn the application of statistics and probability in data science. Students will be able to analyze big data and make data-driven predictions through probabilistic modeling and statistical inference. Finishing this Post Graduate Diploma will prepare for job titles such as : Data Scientist, Data Analyst, Business Analyst, BI Analyst, Data Project Manager, and Data Engineer
The GCA AdvantageÂ
Guided Classroom
Mentorship from Industry Experts
Career Counselling
Industrial Projects
Industrial Discussions and Guest Lectures
Soft Skill Development Workshops
Networking and Events
Live Workshops
Credential Certification
Graduation Ceremony
Internship and Placement Support
Curriculum
Brief Description of all courses.
Data Science and Analytics Fundamentals
20 hours per week, for 8 weeks
Learn about the different aspects of data science, from business applications to the technology needed for data science. Via case studies, students can gain an understanding of descriptive, predictive, and prescriptive analytics, as well as their real-world applications.
Python for Data Science
20 hours per week, for 8 weeks
Learn the basics of the Python programming language from the ground up, as well as how to use it to analyze data. Students can learn how to modify, evaluate, and visualize complex datasets using Python resources such as Pandas, Git, and Matplotlib.
Probability and Stat in Data Science
20 hours per week, for 8 weeks
Understand and gain insights from data using statistical and probabilistic methods. With this introduction to probabilistic models, students can gain foundational knowledge of data science, including random processes and the fundamental elements of statistical inference.
Machine Learning Fundamentals
20 hours per week, for 8 weeks
Learn about Machine Learning algorithms and how to build ML applications for data-driven modeling, prediction, and decision-making. Via hands-on Python projects, students will receive an in-depth introduction to the field of machine learning, from linear models to deep learning and reinforcement learning.
Big Data Analytics
20 hours per week, for 8 weeks
Learn how to use Jupyter notebooks, MapReduce, and Spark as a forum to analyze massive datasets. Student will learn Big Data Technologies and accomplish a project in Big Data.
Applied Capstone Project
20 hours per week, for 8 weeks
In this final evaluation, Student will be able to solidify and demonstrate your skills and abilities in probability, data processing, statistics, and machine learning.
Admission Requirements
We invite applications from motivated candidates:- With a proven record of personal and academic achievement.
- Passed with minimum 50% aggregate marks in B.E. or B.Tech (any discipline) or BSIT (Bachelor of Science in Information Technology) or BIM (Bachelor of Information Management) or BCA (Bachelor of Computer Application) or BCIS (Bachelors in Computer Information Systems) or BSc. (Mathematics / Physics) from a recognized university
- Foundational mathematical and statistical knowledge
- Basic programming skills.
- With a good level of proficiency in English
- Professional experience is a plus, but it is not a requirement for admission.
Syllabus
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The Way Ahead
Start Your Company
Get Hired
Pursue Master’s Degree
Admission Process
Apply Online
Appear in Interview
Get Shortlisted and Receive Offer Letter
Confirm your seat and begin with prep- courses
Fee Structure  Inquiry
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