Python: Big Data Analytics & Algorithmic Stock Trading / Backtesting

"Python: Big Data Analytics & Algorithmic Stock Trading / Backtesting" is an advanced course designed to teach you how to leverage Python for analyzing large financial datasets and developing algorithmic trading strategies. You’ll learn to process and visualize big data, implement and backtest trading algorithms, and evaluate their performance. With practical exercises and real-world case studies, this course equips you with the skills needed to create, test, and optimize trading strategies, preparing you for a career in quantitative finance and data-driven trading.

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05:18:43 Hours

86 Enrolled

    • (4.82 | 17 Reviews)

English

Last updated

Mon, 29-Jul-2024

Course description

Course Overview

"Python: Big Data Analytics & Algorithmic Stock Trading / Backtesting" is a comprehensive course designed to equip learners with advanced skills in using Python for big data analytics and algorithmic trading. The course covers the principles and techniques for analyzing large financial datasets, implementing algorithmic trading strategies, and backtesting these strategies to evaluate their performance. Participants will gain hands-on experience with Python libraries such as Pandas, NumPy, and scikit-learn, and learn how to handle, process, and analyze vast amounts of financial data. By the end of the course, you will be proficient in developing, testing, and optimizing trading algorithms for real-world applications.

Key Learning Objectives

  1. Master Big Data Analytics: Learn to manage and analyze large financial datasets using Python and big data tools.
  2. Algorithmic Trading Development: Develop and implement algorithmic trading strategies using Python.
  3. Backtesting Techniques: Gain skills in backtesting trading algorithms to assess their effectiveness and performance.
  4. Data Processing and Visualization: Acquire techniques for processing, cleaning, and visualizing financial data for analysis.
  5. Performance Evaluation: Understand methods for evaluating and optimizing trading strategies based on backtesting results.

Requirements

  • Proficiency in Python programming and familiarity with basic data analysis concepts.
  • Understanding of financial markets and trading principles.
  • Access to a computer with Python installed and relevant libraries such as Pandas, NumPy, and scikit-learn.
  • Basic knowledge of big data tools and techniques (beneficial but not required).

Outcomes

  1. Big Data Skills: Ability to handle and analyze large financial datasets efficiently using Python.
  2. Algorithmic Trading Expertise: Competence in developing and implementing sophisticated trading strategies.
  3. Backtesting Proficiency: Skills in backtesting and refining trading algorithms to ensure robustness and effectiveness.
  4. Data Processing Abilities: Experience in processing, cleaning, and visualizing financial data to derive actionable insights.
  5. Optimization Techniques: Understanding of performance evaluation methods for optimizing trading strategies based on backtesting outcomes.

Certification

Upon successful completion of the "Python: Big Data Analytics & Algorithmic Stock Trading / Backtesting" course, participants will receive a Certificate of Achievement. This certification validates your advanced skills in utilizing Python for big data analytics and algorithmic trading. It demonstrates your ability to develop, backtest, and optimize trading algorithms, providing a valuable credential for advancing in the fields of data science and quantitative finance.

What will i learn?

  • Big Data Skills: Ability to handle and analyze large financial datasets efficiently using Python.
  • Algorithmic Trading Expertise: Competence in developing and implementing sophisticated trading strategies.
  • Backtesting Proficiency: Skills in backtesting and refining trading algorithms to ensure robustness and effectiveness.
  • Data Processing Abilities: Experience in processing, cleaning, and visualizing financial data to derive actionable insights.
  • Optimization Techniques: Understanding of performance evaluation methods for optimizing trading strategies based on backtesting outcomes.

Requirements

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Ella Wood

09-Aug-2024

5

This advanced course excels in teaching practical skills for analyzing large financial datasets and developing effective trading strategies, with hands-on exercises and real-world case studies that prepare you for a successful career in quantitative finance.

Emma Bell

09-Aug-2024

5

Transformative course! Master data analytics and trading strategies effectively.

George Richardson

09-Aug-2024

5

This advanced course exceeded my expectations! The practical exercises and case studies provided hands-on experience with big data in finance. I gained valuable skills in algorithm development and backtesting that truly prepared me for a career in quantitative finance. Highly recommend for anyone serious about data-driven trading!

Donna Bailey

09-Aug-2024

5

This advanced course excels in teaching practical skills for analyzing large financial datasets and developing algorithmic trading strategies. With hands-on exercises and real-world case studies, it effectively prepares learners for a career in quantitative finance, making complex concepts accessible and applicable. Highly recommended for aspiring traders.

Grace Reyes

09-Aug-2024

5

This advanced course is a game-changer for anyone looking to master financial data analytics. With hands-on exercises, real-world case studies, and expert insights, you'll gain invaluable skills in algorithmic trading and strategy optimization, setting you up for success in quant finance.

Aria Morris

09-Aug-2024

3

This advanced course excels in practical exercises and real-world case studies, effectively bridging theory with application. However, some topics could benefit from deeper exploration, and pacing may be challenging for beginners unfamiliar with Python or financial concepts.

Megan Gutierrez

08-Aug-2024

4

This advanced course offers a comprehensive exploration of using Python for big data analytics and algorithmic trading. The practical exercises and real-world case studies really enhance understanding, enabling you to develop and backtest effective trading strategies. While the content is robust, incorporating more interactive elements, like live coding sessions, could further engage participants and deepen learning. Highly recommended!

Cynthia Cox

08-Aug-2024

5

An exceptional course that expertly combines big data analytics and algorithmic trading, providing invaluable skills for aspiring quantitative finance professionals.

Arthur Gomez

07-Aug-2024

5

This advanced course offers a robust foundation in leveraging Python for financial datasets and algorithmic trading. The combination of practical exercises and real-world case studies truly enhances the learning experience. I gained invaluable skills in big data processing, visualization, and strategy backtesting. The engaging content and hands-on approach prepare you well for a successful career in quantitative finance and data-driven trading. Highly recommend for anyone serious about this field!

David Wood

07-Aug-2024

5

This course was exceptional! The comprehensive approach to big data analytics and algorithmic trading offered invaluable insights into real-world applications. The hands-on exercises and engaging case studies made complex concepts accessible and practical. I now feel confident in creating and optimizing trading strategies, truly preparing me for a career in finance!

Richard Lopez

06-Aug-2024

5

This advanced course effectively combines big data analytics with algorithmic trading techniques, offering hands-on exercises and real-world case studies for a robust learning experience in quantitative finance.

Laura Long

06-Aug-2024

5

This advanced course is a must for anyone looking to excel in quantitative finance. The hands-on approach to processing and visualizing large financial datasets, coupled with the practical implementation and backtesting of trading strategies, truly sets it apart. The real-world case studies provide invaluable insights, ensuring you're well-equipped to tackle challenges in data-driven trading. This course offers the skills needed for a successful career in finance!

Melissa Edwards

06-Aug-2024

5

This advanced course exceeded my expectations! The comprehensive coverage of Python for financial data analysis is exceptional, blending theory with practical exercises. The focus on developing and backtesting algorithmic trading strategies was particularly rewarding, providing real-world applications that enhanced my understanding. The instructor’s expertise and engaging teaching style made complex concepts accessible. I now feel confident tackling challenges in quantitative finance and data-driven trading. Highly recommended!

Michael Gutierrez

03-Aug-2024

5

An exceptional course that empowers you to master big data analytics and algorithmic trading, equipped with practical exercises and real-world case studies for aspiring quantitative finance professionals.

Sean Johnson

02-Aug-2024

5

An invaluable course for mastering data analysis and developing successful trading strategies using Python.

Melissa King

01-Aug-2024

5

This advanced course offers an incredible journey into financial analytics! Engaging content, practical exercises, and real-world case studies make mastering data-driven trading strategies both enjoyable and rewarding. Highly recommended!

Susan Long

30-Jul-2024

5

This advanced course excels in teaching practical Python skills for analyzing large financial datasets and developing algorithmic trading strategies. With hands-on exercises and real-world case studies, it effectively prepares students for careers in quantitative finance, focusing on data processing, visualization, and performance evaluation. Highly recommended!

$9.99

$109.99

Lectures

32

Skill level

Beginner

Expiry period

Lifetime

Certificate

Yes
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