Finance Practitioners and Machine Learners eager to learn ML techniques in Finance and Implementation of ML projects in Finance.

### 09:00 - 10:30 | Part 1

**Quantitative Finance**

- Review Quantitative Finance
- Alternative data

**Machine Learning Modeling**

- Mathematics of Machine Learning
- Machine Learning Modeling Framework

### 10:45 - 12:00 | Part 2

**Supervised Learning: Classification**

- Logistic Regression and Softmax Regression
- SVM's and CART's

**Ensembles**

- Boosting and Bagging: Random Forests
- AdaBoost + XG Boost

### 12:00 - 13:00 | Lunch Break

### 13:00 - 14:30 | Part 3

**Supervised Learning: Regression**

- Modern Linear Regression
- Non-Linear Regression
- Neural Networks
- Deep Neural Networks

### 14:30 - 16:00 | Part 4

**Supervised Learning: Deep Learning**

- Mathematics of Deep Learning
- Deep Learning Architectures

**Reinforcement Learning Natural language Processing**

- Sentiment analysis - NLTK

### 16:00 - 17:30 | Practical

**Python and Exercises**

### Outcome

Mathematics + Python + Applications

### Prerequisites

- laptop with Python installed