" True data science goes beyond the ‘what’ and delves into the ‘why "
Data Science involves extracting insights and knowledge from data through various analytical, statistical, and computational techniques. This course provides comprehensive training in data analysis, visualization, and machine learning, using tools like Python, R, and SQL. You’ll learn to handle large datasets, create predictive models, and transform raw data into actionable insights for decision-making and problem-solving.
Relevance
Unlocking the power of data through science is like learning to read the language of the future.
Data-Driven Decision Making
Data science empowers organizations to make informed decisions based on data analysis and predictive insights.
High Demand
Skilled data scientists are in high demand in industries such as finance, healthcare, marketing, and technology.
Versatile Skill Set
Learn a versatile set of skills including statistical analysis, data visualization, and machine learning.
Transformative Impact
Data science enables the transformation of raw data into actionable insights, driving business growth and innovation.
AI-Driven Fraud Detection
Leveraging AI models to detect unusual transaction patterns, helping prevent fraud and secure online payment systems.
Time Series Analysis
Learn techniques for analyzing and forecasting time-dependent data, ideal for financial and sales forecasting tasks.
Become a data wizard—join our data science course and turn raw data into powerful stories !
TOPICS INCLUDED
- Data Analysis with Python ( Numpy , Pandas )
- Data Visualisation ( matplotlib , Seaborn )
- Statistical Analysis
- Machine Learning with scikit-learn
- Big Data Tools ( Handoop , Spark )
- SQL and Database Management
- Predective Modeling
- Probability and Statistics
- Data story telling and visualisation tools ( Tableau , Power BI )
- NoSQL Database
- And more....
PROGRAM DETAILS
The training program lasts 6 months, and the sessions will be conducted each weekdays as 2-hour sessions. Online sessions will be made available if necessary.
Module-Based Learning: Divided into foundational, intermediate, and advanced levels. Each module covers specific topics, from statistics and Python basics to machine learning and deep learning.
A final project integrating all skills learned, allowing students to develop a complete data science solution from data collection to model deployment.
Learning Support
- Live Sessions: Weekly interactive sessions with instructors and mentors.
- Dedicated Mentorship: One-on-one mentorship to help with project work and understanding key concepts.
- Peer Collaboration: Collaborative group work on projects and discussion forums for peer learning.
Certification
- Data Science Certification: A recognized certificate upon completion, proving proficiency and skill in data science to potential employers.
