Data Science
- Master Python, Statistics, Machine Learning & Deep Learning
- Hands-on projects with real-world datasets & case studies
- Data Visualization using Power BI, Tableau & Matplotlib
- Placement support with resume building & interview preparation
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Course Curriculum
- Introduction to Data Science & Data Analysis
- Python for Data Science (NumPy, Pandas)
- Statistics & Probability for Data Analysis
- Data Cleaning & Preprocessing Techniques
- Machine Learning Algorithms (Supervised & Unsupervised)
- Data Visualization (Matplotlib, Seaborn, Power BI)
- Model Evaluation & Real-time Project Implementation
- Introduction to Cloud Computing & AWS Infrastructure
- Identity and Access Management (IAM)
- Amazon EC2 & Virtual Servers
- Amazon S3 Storage & Data Management
- Virtual Private Cloud (VPC)
- Load Balancing & Auto Scaling
- Database Services (RDS, DynamoDB)
- Azure Fundamentals & Cloud Concepts
- Azure Active Directory (Azure AD)
- Role-Based Access Control (RBAC)
- Virtual Machines & Compute Services
- Storage Accounts & Data Services
- Virtual Networks & Security
- Monitoring & Backup Services
- Introduction to Google Cloud Platform
- Projects, Billing & Resource Hierarchy
- Identity & Access Management (IAM)
- Compute Engine & Virtual Machines
- Kubernetes Engine (GKE)
- Cloud Storage Services
- Cloud Databases (SQL & NoSQL)
- CI/CD Pipeline Concepts
- Git Version Control
- Jenkins Build Automation
- Docker Containerization
- Kubernetes Orchestration
- Infrastructure as Code (Terraform)
- Automation & Monitoring Tools
- Career Guidance & Job Roles
- Resume Building
- LinkedIn Optimization
- Mock Interviews (Tech & HR)
- Interview Q&A Preparation
- Soft Skills & Communication
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