Internship
We are providing internships and training programs to UG and PG engineering students. In these programs, students can undergo training on recent technologies and projects related to learned technology.
Data science using R
- Introduction to Business Analytics
- Introduction to R Programming
- Data Structures
- Data Visualization
- Statistics for Data Science I
- Statistics for Data Science II
- Regression Analysis
- Classification
- Clustering
- Association
Machine learning using python
- Introduction to Artificial Intelligence and Machine Learning
- Data Wrangling and Manipulation
- Supervised Learning
- Feature Engineering
- Supervised Learning Classification Lesson 6. Unsupervised Learning
- Time Series Modeling
- Ensemble Learning
- Recommender Systems
- Text Mining
Data visualization using Tableau
- Connect to and Customize Data
- Organize Data and Create Filters
- Build Common Views
- Map Geographic Data
- Create Calculated Fields
- Apply Table Calculations
- Apply Analytics
- Work with Multiple Data Sources
- Create Dashboards and Stories
- Share and Publish Content
Parallel computing using MPI
- Introduction to parallel computing
- Parallel computer architectures
- Parallel computing models
- MPI basics
- MPI point-to-point communication
- MPI collective communication
- Parallel computing using MPI
Python programming
- Python basics
- Flow Control
- Functions
- Python modules
- Lists
- Tuple
- References
- Dictionaries
- Exception Handling
- Manipulating strings
- Reading and Writing Files
Data science using python
- Data Science Overview
- Data Analytics Overview
- Statistical Analysis and Business Applications
- Python Environment Setup and Essentials
- Mathematical Computing with Python (NumPy)
- Scientific Computing with Python (Scipy)
- Data Manipulation with Pandas
- Machine Learning with Scikit–Learn
- Natural Language Processing with Scikit Learn
- Data Visualization in Python using Matplotlib