Course Overview
This comprehensive Data Science course is designed to equip learners with the essential tools and techniques to solve real-world problems across industries such as finance, e-commerce, healthcare, and more. The program integrates theoretical foundations with hands-on learning through industry-based projects, ensuring participants can apply data science concepts in professional settings.
Learning Objectives
By the end of the course, participants will be able to:
- Analyze and manipulate large datasets using Python and R.
- Build and deploy machine learning models for predictive analytics.
- Develop data-driven solutions to complex business problems.
- Implement deep learning and AI models for various industries.
- Utilize cloud-based tools and APIs to manage data pipelines and model deployment.
- Optimize decision-making through data visualization and business intelligence tools.
Key Modules
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Data Science Fundamentals
Learn the basics of statistics, probability, and linear algebra essential for data science. -
Programming for Data Science
Master Python and R for data wrangling, analysis, and visualization. -
Industry-Specific Data Analytics
- Finance: Portfolio optimization, risk analysis, and algorithmic trading.
- E-commerce: Customer segmentation, product recommendation systems, and sales forecasting.
- Healthcare: Predictive modeling for patient outcomes and disease diagnosis.
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Machine Learning & AI in Practice
Build supervised and unsupervised models using real industry datasets, including classification, regression, clustering, and reinforcement learning techniques. -
Big Data and Cloud Computing
Introduction to Hadoop, Spark, and cloud services like AWS, GCP, and Azure for managing large-scale data and machine learning workflows. -
Advanced Topics
- Deep Learning with Neural Networks.
- Natural Language Processing (NLP) for business insights.
- Time Series Forecasting for demand and supply planning.
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Capstone Industry Project
Apply everything you've learned to a real-world, industry-specific data science problem. Choose from domains like financial analysis, e-commerce personalization, or healthcare diagnostics. Work on live datasets, collaborate with industry professionals, and present your solutions to stakeholders.
Who Should Enroll?
- Aspiring Data Scientists looking to enter the industry.
- Professionals transitioning from other domains like IT, finance, or business analytics.
- Data professionals wanting to expand their expertise into machine learning and AI.
- Business managers aiming to leverage data for strategic decision-making.
Industry Collaboration
Throughout the course, you’ll engage in case studies and projects designed in collaboration with leading companies. You’ll gain exposure to real-world business challenges, enabling you to become job-ready by the end of the program.
- Teacher: Admin User