Data Science
Course Registration
Data Science Curriculum
- Introduction to Python
- Data Structures and Libraries (NumPy, Pandas)
- Data Wrangling and Preprocessing
- Data Visualization (Matplotlib, Seaborn)
- Working with APIs and Web Scraping
- Descriptive Statistics
- Inferential Statistics
- Probability Theory
- Hypothesis Testing
- Exploratory Data Analysis
- Supervised & Unsupervised Learning
- Regression & Classification Techniques
- Clustering & Dimensionality Reduction
- Model Evaluation & Tuning
- Feature Engineering & Selection
- Neural Networks Basics
- Convolutional Neural Networks (CNNs)
- Recurrent Neural Networks (RNNs)
- Natural Language Processing (NLP)
- Transfer Learning & Advanced Models
- End-to-End Data Science Project
- Model Deployment using Flask/Django
- Cloud Deployment (AWS, GCP, Azure)
- Data Engineering Concepts
- Real-time Analytics & Big Data Tools
Projects
CRM / HRMS
After completing the course, we work on projects based on real-world standards to solidify your learning.
Tools & Technologies:
✓ Java
✓ STS
✓ SpringBoot
✓ Postman
✓ ATOM
✓ MySQL
✓ React
✓ Docker
✓ Git
✓ Github
✓ Trello
✓ VS Code
Ecommerce / Finance
After completing the course, we work on projects based on real-world standards to solidify your learning.
Tools & Technologies:
✓ Java
✓ STS
✓ SpringBoot
✓ Postman
✓ ATOM
✓ MySQL
✓ React
✓ Docker
✓ Git
✓ Github
✓ Trello
✓ VS Code
We Build Your Profiles to Help You Stand Out
Github
For freshers, GitHub plays a significant role in showcasing skills
Portfolio
For freshers, a portfolio demonstrates practical experience and personal projects effectivelyCertificate
