Overview

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This course features Coursera Coach! A smarter way to learn with interactive, real-time conversations that help you test your knowledge, challenge assumptions, and deepen your understanding as you progress through the course. In this course, you'll take your trading bot to the next level by incorporating advanced strategies and automation. You'll learn how to use mathematical, logical, and comparison operators to build complex decision-making processes for your bot. The course also covers support and resistance analysis, teaching you to identify key price levels in the market for better trade execution. You will then dive deep into candlestick pattern analysis, turning these patterns into actionable data for decision-making. Additionally, you'll explore advanced statistical methods such as linear and polynomial regression, helping you design algorithms that can make accurate market predictions. The course also covers market trends and volatility, providing the knowledge to adjust your trading strategy dynamically based on market conditions. The course culminates in learning how to set up looping logic to automate repetitive tasks and backend workflows in your trading bot. From retrieving real-time asset prices to automating complex tasks, you will master the skills necessary to build an intelligent, fully automated trading system. Whether you're automating trades or analyzing complex market data, this course will equip you with the tools to take your trading bot to new heights. This course is intended for individuals who have a foundational understanding of trading bots and no-code development. You should have completed the introductory parts of trading bot creation or have experience with similar platforms. The course is designed for intermediate learners looking to expand their skills in automation, algorithmic trading, and data analysis. By the end of the course, you will be able to design and implement advanced trading strategies, automate complex tasks, and integrate statistical analysis for improved trading decision-making.

Syllabus

Bot: Creating the Math Strategy

In this module, we will cover essential math, comparison, and logical operators, showing you how to apply them in your trading bot’s strategy and manipulate data for better decision-making.

Bot: Support & Resistance

In this module, we will guide you through the process of creating and visualizing support and resistance levels, helping you understand market dynamics and strengthening your trading strategies.

Bot: Candlestick Analysis

In this module, we will show you how to translate candlestick patterns into mathematical data, allowing you to enhance your trading bot’s strategy by integrating pattern recognition.

Bot: Algorithm Design & Statistics

In this module, we will explain how to design algorithms without code and use regression techniques to create more accurate and complex data models for your trading bot.

Bot: Identifying State / Trend

In this module, we will cover how to identify and assess market trends, volatility, and overall market state, ensuring that your bot’s strategy is adaptable and responsive.

Automations: Looping Logic

In this module, we will introduce you to looping logic and backend workflows, showing you how to automate tasks such as price retrieval and complex trading operations within your bot.

Conclusion

In this final module, we will summarize the main takeaways from the course and provide guidance on the next steps in your journey to refining and scaling your trading bot.