Advanced Programme in Data Science

Course Overview

• Course Duration:10-12 Months (Flexible timings available).
• Eligibility: Graduates working professionals aspiring data scientists.
• Aspiring data scientists.

Advanced Programme in Data Science Training Course

• Learn the fundamentals of Advanced Programme in Data Science, statistics, and data analytics.
• Perform data preprocessing, cleaning, and transformation for real-world datasets.
• Master machine learning algorithms for predictive and classification modeling.
• Work with Advanced Programme in Data Science, Python, R, and SQL for data analysis and model building.
• Create visual insights using Power BI and Tableau dashboards.
• Prepare for Advanced Programme in Data Science Certifications and data-driven career opportunities.

Overview of Advanced Programme in Data Science

The Advanced Programme in Data Science is designed for learners, analysts, and professionals seeking to advance their careers in analytics and AI. This program combines the technical depth of programming with the analytical rigor of business intelligence, providing you with the specialized technical expertise needed to advance your career.

Through hands-on labs, case studies, and live projects, learners gain end-to-end knowledge of the Advanced Programme in Data Science lifecycle — from data collection and analysis to machine learning and deployment. By the end of the program, you'll earn your Advanced Data Science credential preparation and be career-ready for high-demand roles such as Data Scientist, Analyst, or AI Engineer.

Module 1 – Introduction to Data Science

• Overview of data science, its importance, and real-world applications.
• Required skills and career paths in the data science field.
• Introduction to tools and technologies used by data scientists.

Module 2 – Mathematics for Data Science

• Linear algebra essentials: vectors, matrices, and transformations.
• Statistics: descriptive, inferential, hypothesis testing.
• Calculus: partial derivatives, gradients, and optimization.

Module 3 – Programming Fundamentals in Python

• Python basics: data types, control structures, functions.
• Object-oriented programming (OOPs), threading, file handling.
• Data scraping and handling data in Python.

Module 4 – Data Handling and SQL

• Working with libraries: NumPy and Pandas.
• SQL: MySQL queries (DML, DDL, TCL, DQL), NoSQL concepts.
• Connecting Python with databases for real-time projects.

Module 5 – Data Visualization Techniques

• Introduction to data visualization and its impact.
• Using Matplotlib and Seaborn to create charts and plots.
• Visual analytics and storytelling with data.