Data Science Super Specialization
With our most popular program- Data Science Super Specialization- you will become a Data Science expert by covering various concepts like Python, Statistics, Machine Learning, R Programming and Tableau.
You can register for one of our free events to interact with our faculty or also attend a trial class.
Industry immersion sessions enable students to interact with Big Data Analytics practitioners from top companies like Twitter, Facebook, Vodafone, Barclays, PwC, Zomato, etc. to make them understand how their organizations use Big Data & Data Science.
Click here to view one such session taken by Sandeep Tompala- Senior Manager- Data Consulting, Vodafone.
- Next Batch Start Date: July 8th
- Class Timing: Sat, Sun (10:30 AM- 12:30 PM IST)
- Mode: Online
- Duration: 14 weeks
- Certification of Completion: Yes
- Certification: Yes, Subject to clearing exam
Data Science Super Specialization 0/24
- 1. Data Science Intro, Fundamentals, Use Cases
- 2. Python Basics
- 3. Statistics 1
- 4. Python Advanced
- 5. Exploratory Data Analysis
- 6. ML Intro, Fundamentals, Use Cases
- 7. Statistics 2
- 8. Supervised, Unsupervised Learning,Linear Regression
- 9. Logistic Regression
- 10. Decision Trees ,Random Forest
- 11. Bagging & Boosting, Cost Function, Gradient descent
- 12. Modelling Techniques
- 13. KNN,Naïve Bayes
- 14. Support Vector Machine (SVM)
- 15. Unsupervised Learning, Clustering , K-means clustering
- 16. Time series components,Moving averages,Classical decomposition,Simple exponential smoothing,Holt’s method,Winters method
- 17. Holt-Winters seasonal method ,Stationarity and differencing ,Autoregressive models , Moving average models
- 18. ARIMA modelling
- 19. Tableau – Introduction
- 20. Tableau – Data Visualisation fundamentals
- 21. Tableau–Analytics concepts –1
- 22. Tableau-Analytics concepts – 2
- 23. Tableau – Predictive Analytics with R programming tool
- 24. Tableau – Project workshop (POC)
All classes take place over the weekends in the mornings. There’ll be one class of 2 to 2.5 hours on Saturdays and Sundays each. This means that you can now acquire in-demand skills without compromising on your schedule.