Introduction
Data in today’s world is bigger than ‘oil’ or ‘gold’. Organizations primarily rely on data for business insight, customer acquisition, product development, innovation and more. Data-driven insights and decisions make or break the deal across business processes from lead generation, sales funnels, pattern recognition, risk prediction, fraud detection, operational automation, employee engagement and more.
STL’s PG Diploma in Data Science program equips candidates with skills and knowledge for better decision making, strategy and operations with data-driven insights to address real-world business problems in real-time.
STL Academy emphasizes usage of latest analytical concepts to solve business problems. In the course of this program, you will learn to harness the strength of Data Science tools on cutting-edge technology platforms.
Curriculum
- Introduction to Data Science
- Data Visualization
- Data Mining and Data Warehouse
- Decision Analytics
- Essential Tools for Data Science
- Deep Learning
- Big Data
- Machine Learning
- Real Time Data Processing
- Data Mining and Data Warehouse
- Business Analytics (Data Analysis)
- Deep Learning
- Machine Learning
- Supervised Learning Methods
- Unsupervised Learning Methods
- Stochastic Approximation Algorithms
- Classroom sessions, simulation exercises, case studies
- Assignments and discussions
- Projects (On-site and off-site)
- Analytics Consultant
- Analytics Manager
- Data Analyst
- Reporting Analyst
- Research Executive
- Data Scientist
- ML Engineer
- Data Engineer
- AI Engineer
- Statistician
Key Learning Outcomes
Why STL
studies.
Post Successful
Completion of
this course
Eligibility Criteria for Admission in PG Diploma Courses of STL Academy
Any student who:
- Is a B.Tech with 50% or higher.
- Is a graduate in any quantitative discipline like engineering, mathematics, commerce, sciences, statistics, economics etc. with 50% or higher.
- Has cleared the STL – STEM (Sterlite Technical Eligibility Milestone) Test with 60% or higher.
- Can read and write in English.
- Is passionate about technologies.
For Data Science, the candidate should understand basic concepts of Math and Statistics, along with above requirements.
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Selection and Admission Process
