International Institute of Information Technology Bangalore
- University
- Co - Education
- ESTD 1999
- Engineering
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Postgraduate Diploma in Data Science
Postgraduate Diploma in Data Science
Course
Post Graduate Diploma in Data Science is a nine month part-time programme aimed at creating the next generation Analyst and Data Scientist. For students interested in analytics, technology firms, regulators, consulting and universities across the globe. PGDDS is an extremely unique opportunity to obtain first-hand knowledge, both theoretical and practical, from NISM an institute established by SEBI, the market regulator and prestigious Department of Economics (Autonomous), University of Mumbai. The faculty, consisting of academicians and practitioners, has the capability to deliver a high-quality and cutting-edge programme to the students looking for knowledge and skill-sets as a solid foundation.
Eligibility: Graduates with a minimum of 50% marks can take up this program
Duration: The 11-month online PG Diploma, co-developed by IIIT Bangalore and UpGrad, covers the depth and breadth of the subject in the form of interactive lectures, live sessions and a 3-month capstone project mentored by industry professionals.
Programme Highlights
This course provides participants with:
• An understanding of the structure of datasets and databases, including "big data"
• The ability to work with datasets and databases
• An introduction to programming languages and basic skills in the R/ Python statistical program
• The ability to analyze data using statistical and machine learning methods.
• The ability to apply to analyze large financial data for decision making purpose
Curriculum
Preparatory course
The prep content covers modules on Data Analysis on Excel, Introduction to Python , Python for Data Science and Visualization using Tableau.
Statistics and Exploratory Data Analytics
This course covers Inferential Statistics, Hypothesis Testing, Assignment: Statistics and Hypothesis Testing and Exploratory Data Analysis
Machine Learning 1
In this module of Machine Learning you will learnLinear Regression, Logistic Regression, Unsupervised learning: Clustering and Unsupervised Learning: Principal Component Analysis
Machine learning 2
In this course you will learnModel Selection, Model Selection - Practical Considerations, Tree Model, Advanced Regression and 2 optional modules on Time Series and Neural networks
Career Opportunities
- Financial Analytics,
- Data Analyst,
- Marketing: Managers,
- Market Research Analyst and Specialist,
- Research Scientist.
