Data Science

Data Science is an advanced technology programme focused on extracting meaningful insights and building intelligent solutions from data.

The course combines Python programming, statistics, data analysis, visualization, machine learning and practical projects to help learners understand the complete data science workflow from raw data to predictive models.

The Data Science programme provides a practical learning path covering programming, data preparation, statistical analysis, visualization and machine learning.

Learners work with Python and popular data science libraries to clean datasets, explore patterns, visualize information and develop machine learning models.

The programme emphasizes practical implementation through projects and real-world datasets, helping learners build a strong foundation for advanced data science and AI learning.

Course Name: Data Science

Training Level: Beginner to Advanced

Mode: Classroom + Practical + Project-Based Training

Key Training Areas:

• Python Programming
• Python for Data Science
• NumPy
• Pandas
• Data Cleaning
• Exploratory Data Analysis
• Statistics for Data Science
• Data Visualization
• Matplotlib & Seaborn
• SQL & Databases
• Machine Learning Fundamentals
• Supervised Learning
• Unsupervised Learning
• Regression
• Classification
• Clustering
• Model Evaluation
• Feature Engineering
• Introduction to Artificial Intelligence
• Real-World Data Science Projects

Practical Training:
Learners work with datasets and develop complete data science projects from data preparation to model evaluation.

Project-Based Learning:
Students build portfolio projects that demonstrate practical knowledge of Python, analytics and machine learning.

Basic computer knowledge and logical thinking are recommended.

Basic mathematics and statistics knowledge can be helpful. Prior programming experience is useful but not mandatory for beginners.

Learners should be willing to practice Python programming, mathematics, statistics and machine learning concepts.