Publico Alvo

• Cientista de Dados Financeiros
• Analista Quantitativo
• Analista de Gestão de Riscos
• Gerente de portfólio
• Banqueiro de investimento
• Analista de crédito
• Engenheiro de aprendizado de máquina financeiro
• Gerente de ativos
• Comerciante Algorítmico
• Modelador Financeiro
• Especialista em Business Intelligence Financeiro
• Desenvolvedor de tecnologia financeira
• Analista de Operações Bancárias
• Analista de fundos de hedge
• Especialista em Insurtech

Pre-Requisitos

• Pelo menos níveis O e acima da educação
• Ler, escrever, falar e entender inglês

Materiais

Conteúdo Programatico

Get Started on Python

• Overview of Python
• Set Python
• Code Your First Python Script

Data Types

1. Number
2. String
3. List
4. Tuple
5. Dictionary
6. Set

Operators

1. Arithmetic Operators
2. Compound Operators
3. Comparison Operators
4. Membership Operators
5. Logical Operators

Control Structure, Loop and Comprehension

1. Conditional
2. Loop
3. Iterating Over Multiple Sequences
4. Comprehension

Function

1. Function Syntax
2. Return Values
3. Default Arguments
4. Variable Arguments
5. Lambda, Map, Filter

Modules & Packages

1. Import Modules and Packages
2. Python Standard Packages
3. Third Party Packages

Data Preparation

1. Data Analytics with Pandas
2. Pandas DataFrame and Series
3. Import and Export Finance Data
4. Filter and Slice Finance Data
5. Clean Missing Data

Data Transformation

1. Create Computed Data Column
2. Join Finance Data with Concat, Append and Merge
3. Aggregate Data with Groupby and Pivot Table

Data Visualization

1. Visualize Time Series Data with Line Plot
2. Visualize Statistical Relationships with Scatter Plot
3. Visualize Categorical Data with Bar Plot and Pie Plot
4. Visualize Variation with Box Plot
5. Visualize Distribution with Histogram

Data Analysis

1. Descriptive Statistics
2. Rolling Window Average Analysis
3. Covariance and Correlation

Advanced Data Analytics

1. Apply
2. Data Piping

Introduction to Deep Learning

1. Overview of Artificial Intelligence (AI) and Deep Learning
2. Evaluation of Data Analytics Platforms for Deep Learning
3. Applications of AI to Finance Services
4. Deep Learning Methodology

Neural Network for Regression

1. What is Neural Network (NN)?
2. Activation Functions
3. Mean Square Error (MSE) Loss Function for Regression
4. Optimization Algorithms
5. Build a Predictive Regression Model for Sales Forecasting

Neural Network for Classification

1. One Hot Encoding and SoftMax
2. Cross Entropy Loss Function for Classification
3. Build a Classification Model for Classifying Currency Notes

Image Classification with Convolutional Neural Network (CNN)

1.  Introduction to Convolutional Neural Network (CNN
2. Build a Image Classification Model for Currency Notes Detection
3. Small Dataset Overfitting Issue
4. Methods to Solve Overfitting Issues
5. Transfer Learning

Time Series Forecasting with Recurrent Neural Network (RNN)

1. Introduction to Recurrent Neural Network (RNN)
2. LSTM and GRU Models
3. Build a Time Series Forecasting Model for Stock Price