create me a course to learn bot trading week by week. Make it as long as you deem necessary. Only plot 5 at a time and prompt me to type "go" for 5 more.
user
week 1: introduction to bot trading
1.1: understanding the basics of trading and financial markets.
1.2: history and evolution of bot trading.
1.3: fundamentals of algorithmic trading and its applications.
1.4: familiarizing with different types of trading bots.
1.5: benefits and risks associated with bot trading.

week 2: building a foundation
2.1: identifying trading strategies and timeframes.
2.2: introduction to apis and their usage in trading.
2.3: understanding data feeds and data storage.
2.4: risk management and position sizing.
2.5: introduction to backtesting methodologies.

week 3: tools and technologies
3.1: popular programming languages for bot trading: python, r, and javascript.
3.2: introduction to trading platforms, libraries, and frameworks.
3.3: hands-on with popular libraries, like ccxt, pandas, and numpy.
3.4: setting up a development environment.
3.5: code repositories and version control with git.

week 4: data analysis and strategy development
4.1: introduction to technical analysis and chart patterns.
4.2: building a simple moving average crossover strategy.
4.3: utilizing advanced indicators and their implementation.
4.4: identifying and validating entry and exit signals.
4.5: incorporating fundamental analysis in your trading strategy.

week 5: backtesting and optimization
5.1: importance of historical data and data quality.
5.2: creating a backtesting framework in python.
5.3: evaluating the performance of your trading strategy.
5.4: parameter optimization and overfitting prevention.
5.5: understanding the concept of walk-forward optimization.

type "go" for the next 5 weeks.
assistant
Week 1: Introduction to Bot Trading
1.1: Understanding the basics of trading and financial markets.
1.2: History and evolution of bot trading.
1.3: Fundamentals of algorithmic trading and its applications.
1.4: Familiarizing with different types of trading bots.
1.5: Benefits and risks associated with bot trading.

Week 2: Building a Foundation
2.1: Identifying trading strategies and timeframes.
2.2: Introduction to APIs and their usage in trading.
2.3: Understanding data feeds and data storage.
2.4: Risk management and position sizing.
2.5: Introduction to backtesting methodologies.

Week 3: Tools and Technologies
3.1: Popular programming languages for bot trading: Python, R, and JavaScript.
3.2: Introduction to trading platforms, libraries, and frameworks.
3.3: Hands-on with popular libraries, like ccxt, pandas, and Numpy.
3.4: Setting up a development environment.
3.5: Code repositories and version control with Git.

Week 4: Data Analysis and Strategy Development
4.1: Introduction to technical analysis and chart patterns.
4.2: Building a simple moving average crossover strategy.
4.3: Utilizing advanced indicators and their implementation.
4.4: Identifying and validating entry and exit signals.
4.5: Incorporating fundamental analysis in your trading strategy.

Week 5: Backtesting and Optimization
5.1: Importance of historical data and data quality.
5.2: Creating a backtesting framework in Python.
5.3: Evaluating the performance of your trading strategy.
5.4: Parameter optimization and overfitting prevention.
5.5: Understanding the concept of walk-forward optimization.

Type "go" for the next 5 weeks.
assistant