This course is part of the Data Science for Investment Professionals Specialization

Anastasia Diakaki

1,843 already enrolled

Offered By

Data Science for Investment Professionals SpecializationCFA Institute

About this Course

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This course is uniquely tailored to the needs of investment professionals or those with investment industry knowledge who want to develop a basic, practical understanding of machine learning techniques and how they are used in the investment process. Incorporating real-life case studies, this course covers both the technical and the “soft skills” necessary for investment professionals to stay relevant. 
In this course, you will learn how to:
-	Distinguish between supervised and unsupervised machine learning and deep learning
-	Describe how machine learning algorithm performance is evaluated
-	Describe supervised and unsupervised machine learning algorithms and determine the problems they are best suited for
-	Describe neural networks, deep learning nets, and reinforcement learning
-	Choose an appropriate machine learning algorithm
-	Describe the value of integrating machine learning and data projects in the investment process
-	Work with data scientists and investment teams to harness information and insights from within large and alternative data sets
-	Apply the CFA Institute Ethical Decision-Making Framework to machine learning dilemmas

This course is part of the Data Science for Investment Professionals Specialization offered by CFA Institute.

Flexible deadlines

Reset deadlines in accordance to your schedule.

Shareable Certificate

Earn a Certificate upon completion

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Coursera Labs

Includes hands on learning projects.

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Course 3 of 3 in the

Data Science for Investment Professionals Specialization

Beginner Level

Background in investment products and firms

Approx. 16 hours to complete

English

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What you will learn

Describe how machine learning applications can address real-world investment problems
Explain machine learning concepts and techniques to a non-expert audience
Utilize the language of data science when working with data scientists and data engineers
Apply the CFA Institute Ethical Decision-Making Framework to machine learning dilemmas

Skills you will gain

Data Science
Ethics
Machine Learning
Communication
Investment

Flexible deadlines

Reset deadlines in accordance to your schedule.

Shareable Certificate

Earn a Certificate upon completion

100% online

Start instantly and learn at your own schedule.

Coursera Labs

Includes hands on learning projects.

Learn more about Coursera Labs

Course 3 of 3 in the

Data Science for Investment Professionals Specialization

Beginner Level

Background in investment products and firms

Approx. 16 hours to complete

English

Could your company benefit from training employees on in-demand skills?

Try Coursera for Business

Instructor

Anastasia Diakaki

Content Director

Professional Learning

1,843 Learners

1 Course

Offered by

CFA Institute

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Syllabus - What you will learn from this course

Week1

Week 1

1 hour to complete

Welcome To Machine Learning for Investment Professionals

1 hour to complete

2 videos (Total 7 min), 2 readings

2 hours to complete

Machine Learning

2 hours to complete

4 videos (Total 32 min), 3 readings, 2 quizzes

4 videos

Introduction to Machine Learning1mWhat is Machine Learning?7mMachine Learning Techniques10mOverfitting and How to Address It12m

3 readings

Case Study: Enhancing Trading Strategy and Execution with Machine Learning15mGo Deeper: Access the AI Pioneers in Investment Management Report10mPreventing Overfitting in Supervised Machine Learning15m

2 practice exercises

Machine Learning Techniques15mMachine Learning Graded Assessment15m

Week2

Week 2

3 hours to complete

Supervised Learning

3 hours to complete

6 videos (Total 37 min), 3 readings, 5 quizzes

6 videos

Introduction to Supervised Learning1mPenalized Regression5mSupport Vector Machine6mK-Nearest Neighbor6mClassification and Regression Tree (CART)9mEnsemble Learning and Random Forest8m

3 readings

Case Study: Sentiment Analysis15mGo Deeper: Access the AI Pioneers in Investment Management Report10mCase Study: Classification of Winning and Losing Funds20m

5 practice exercises

Penalized Regression15mK-Nearest Neighbor15mClassification and Regression Tree (CART)30mEnsemble Learning and Random Forest30mSupervised Learning Graded Assessment20m

Week3

Week 3

2 hours to complete

Unsupervised Learning

2 hours to complete

4 videos (Total 29 min), 2 readings, 2 quizzes

Week4

Week 4

3 hours to complete

Deep Learning

3 hours to complete

4 videos (Total 22 min), 2 readings, 5 quizzes

4 videos

Introduction to Deep Learning1mNeural Networks8mDeep Neural Networks and Reinforcement Learning7mChoosing the Appropriate ML Algorithm3m

2 readings

Case Study: Refining Equity Trading Volume Prediction with Deep Learning10mCase Study: Deep Neural Network-Based Equity Factor Model2m

5 practice exercises

Neural Networks20mDeep Neural Networks and Reinforcement Learning30mDeep Neural Network-Based Equity Factor Model20mChoosing the Appropriate ML Algorithm20mDeep Learning Graded Assessment30m

About the Data Science for Investment Professionals Specialization

This Specialization is uniquely tailored to the needs of investment professionals or those with investment industry knowledge who want to develop a basic, practical understanding of machine learning techniques and how they are used in the investment process. Through the three courses, you will learn techniques for presenting data and importance of the “data story”, produce data visualizations using Python, assess and apply probability concepts to investing scenarios, compare simple time-series models and understand their limitations, discover how machine learning applications can address investment problems, and understand how to apply the CFA Institute Ethical Decision-Making Framework to machine learning dilemmas. All that you learn in this Specialization will give you the knowledge and confidence to explain clearly and “translate” machine learning concepts and their application to real-world investment problems to a non-expert audience and clients.

Frequently Asked Questions

When will I have access to the lectures and assignments?
Access to lectures and assignments depends on your type of enrollment. If you take a course in audit mode, you will be able to see most course materials for free. To access graded assignments and to earn a Certificate, you will need to purchase the Certificate experience, during or after your audit. If you don't see the audit option:
The course may not offer an audit option. You can try a Free Trial instead, or apply for Financial Aid.
The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.
What will I get if I subscribe to this Specialization?
When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.
Is financial aid available?
Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.
Does completing this course give me credit in any CFA Institute Programs?
No. Completing this course or any other courses offered by CFA Institute on Coursera does not count as credit in the CFA Program, CIPM Program, or any other professional certificate or credential offered by CFA Institute.

More questions? Visit the Learner Help Center.

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Machine Learning for Investment Professionals

About this Course

What you will learn

Skills you will gain