Curriculum
- 15 Sections
- 150 Lessons
- 6 Weeks
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- Introduction to Data Science10
- 1.1Introduction to Data Science
- 1.2Data Science Lifecycle
- 1.3Role of a Data Scientist
- 1.4Data Science vs Data Analytics
- 1.5Types of Data
- 1.6Structured and Unstructured Data
- 1.7Data Collection and Data Sources
- 1.8Data-Driven Decision Making
- 1.9Data Science Career Opportunities
- 1.10Setting Up the Data Science Environment
- Python Fundamentals10
- Python for Data Science10
- Exploratory Data Analysis10
- Data Visualization10
- Statistics and Probability10
- SQL for Data Science10
- Machine Learning Fundamentals10
- Data Preprocessing and Feature Engineering10
- Supervised Machine Learning10
- Unsupervised Machine Learning10
- Machine Learning Model Evaluation10
- Advanced Data Science Concepts10
- 13.1Introduction to Deep Learning
- 13.2Neural Network Fundamentals
- 13.3Introduction to Natural Language Processing
- 13.4Text Data Processing
- 13.5Introduction to Computer Vision
- 13.6Introduction to Generative AI
- 13.7Model Deployment Concepts
- 13.8APIs for Data Science Applications
- 13.9Responsible AI and Ethics
- 13.10Data Science Industry Best Practices
- Power BI for Data Science10
- Data Science Live Projects10
- 15.1Sales Prediction Project
- 15.2Customer Churn Prediction
- 15.3House Price Prediction
- 15.4Customer Segmentation Project
- 15.5Marketing Analytics Project
- 15.6Financial Data Analysis
- 15.7Sentiment Analysis Project
- 15.8Machine Learning Classification Project
- 15.9Power BI Analytics Dashboard
- 15.10Final Data Science Capstone Project
Power BI Analytics Dashboard
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