Python and Machine Learning for Financial Analysis

Merge Python, ML and Finance and join the financial analysis game with 20+ hours of top-rated content!

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1 month

Average completion time

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through SDS Club

$ 16.99 $119,99
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Learn from Industry Leaders

Dr Ryan Ahmed’s dual academic background in finance and technology inspired him to create this course. Ryan has held engineering positions at several Fortune 500 companies, including Samsung America and Fiat-Chrysler Automobiles (FCA) Canada. 




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A high demand for Python developers and few qualified candidates make this the ideal programming language to learn today.

Learn an essential industry tool

Python is a vital programming language for machine learning and AI.

Finance & banking are thirsty for AI

This course helps you get practical experience for an industry that needs it.

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  • Get to grips with the programming fundamentals of Python.
  • Understand how to use Python specifically for financial analysis.
  • Learn AI and machine learning applications in the finance & banking industry.
  • Build six practical projects to add to your interview portfolio.
  • A 30-day money-back guarantee, to trial the course risk-free. 
  • Certificate of completion for your LinkedIn profile, to showcase your Python skills to employers.
  • Master Python 3 programming fundamentals for Data Science and Machine Learning with focus on Finance.
  • Master SciKit-Learn library to build, train and tune machine learning models using real-world datasets.
  • Optimize ANNs hyper parameters such as number of hidden layers and neurons to enhance network performance.
  • Master feature engineering and data cleaning strategies for machine learning and data science applications.

Why Should I Take This Course?

Testing while you learn

Understand a popular programming language

A versatile tool for data science projects

Python can be used for financial analysis, computer vision, gaming, robotics, and more. For this course, mini challenges and coding exercises will test your knowledge at course milestones, to help you learn through practice.

High Job Market Demand

AI Skills Gap

Career Opportunities

Ryan Ahmed is a bestselling instructor, teaching science to thousands of students worldwide. He has a PhD in Mechanical Engineering and an MBA in Finance.

Become a Financial Analyst.

Financial analysts in the US can expect to be paid around $116,000 a year.

Average salary

for a financial analyst in the U.S.
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What You Will Get

Expert Instructors

  • Learn from the Industry Leaders
  • 1M+ students
  • 50,000 five-star reviews
  • 49 Courses Rated 4.5+

On-Demand Lifetime Content

  • Learn at your own pace with on-demand video
  • Enjoy lifetime access to the course
  • Available to view on mobiles and TV

Intensive Content

  • Python review
  • 7 hours of on-demand video content
  • 11 articles
  • 5 downloadable resources

Career Credentials

  • Earn a certificate of completion
  • Work with real-world scenarios
  • Add real projects to your portfolio

People Talk About Us

Python’s great advantage for finance & banking

Machine learning and AI have multiple largescale applications in finance & banking, and the industry has been quick to take advantage of any new technology. Utilizing Python has been a particularly fruitful approach for many finance professionals, due to the programming language’s vast capabilities.

With Python, financial analysts can process a huge amount of data for their organization. They can make accurate calculations for risk and trade that improve business operations to a level of sophistication that would not have been possible even five years ago. Major banks like Credit Suisse use Python to: detect fraud, better align their services to their customers’ needs, set up management systems, and
model smart investments.

These developments have all made a huge difference to the fundamental pillars of finance & banking.

Learn the principles of programming in finance

The course all the fundamentals of Python programming. This makes it a useful refresher for Python users who want to work in finance. But it is also useful for anyone who is already in the finance industry and wants to learn Python.

Suitable even for complete beginners, Ryan covers the various data types, variable functions, and file operations that any Python user should expect to see when using the program. Once you’ve grasped the fundamentals, you’ll get a deeper understanding of key Python libraries such as NumPy and Pandas, as well as the visualization tools that you’ll use at the end of your projects, such as Matplotlib, Seaborn, Plotly and Bokeh.

By the end of the course, you’ll have six completed projects to put into your portfolio when you go on the job hunt!

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