Machine Learning for Quant Finance and Algorithmic Trading

### Course Overview
- **Course Title:** Machine Learning for Quant Finance and Algorithmic Trading
- **Instructor:** Raj Chhabria
- **Target Audience:**
  - Finance professionals
  - Data enthusiasts
  - Individuals interested in quantitative finance and algorithmic trading
- **Prerequisites:**
  - Basic understanding of Python Programming Language

### Curriculum Highlights
- **Key Topics Covered:**
  - Complete lifecycle of a Machine Learning Project
  - Financial Market concepts (Derivatives, Asset pricing models, Technical Analysis)
  - Essentials of Machine Learning and Deep Learning
  - Building Trading Strategies using Machine Learning
  - Web Apps and Dashboards using Streamlit
  - Hands-on Coding Projects in Python, Machine Learning, Deep Learning, and Streamlit
- **Key Skills Learned:**
  - Data manipulation and visualization using Pandas, NumPy, Matplotlib, and Seaborn
  - Supervised and unsupervised learning
  - Deep learning techniques
  - Developing and backtesting trading strategies
  - Building interactive web applications and dashboards

### Course Format
- **Duration:** 11 hours on-demand video
- **Format:** Self-paced online course
- **Resources:**
  - 85 downloadable resources
  - Access on mobile and TV
  - Certificate of completion