COURSE DETAILS

The use of data science and machine learning in the investment industry is increasing. Financial firms are using artificial intelligence (AI) and machine learning to augment traditional investment decision making. In this course, we aim to bring clarity on how AI and machine learning are revolutionizing financial services. We will introduce key concepts and, through examples and case studies, will illustrate the role of machine learning, data science techniques, and AI in the investment industry. Rather than just showing how to write code or run experiments in Python, we will provide an intuitive understanding to machine learning with just enough mathematics and basic statistics.

You will learn:

  • Role of Machine Learning and AI in Financial services
  • When do we use Machine learning and AI techniques?
  • What are the key machine learning methodologies?
  • How do you choose an algorithm for a specific goal?
  • Practical Case studies with fully functional code

Delivery:

  • LIVE: Email info@qusandbox.com for upcoming LIVE training dates
  • ON DEMAND: Pre-recorded sessions with interactive videos, slides, demos and fully functional code through Qu.Academy.

Who should attend?

  • Fundamental and quantitative analysts, risk and investment professionals, portfolio managers new to data science and machine learning
  • Financial professionals new to data-driven methodologies
  • Machine learning enthusiasts interested in use cases in fintech and financial organizations

Prerequisites

Participants are expected to have a working knowledge of Python. Please consider taking the Just Enough Python for Data Science in Finance if you don’t know Python.

Combo offer

This course is a part of the QuantUniversity Machine Learning and AI Risk Certificate Program. Avail additional discounts by enrolling in the Certification program.

QuantUniversity has partnered with (Professional Risk Managers' International Association) PRMIA to offer this course and is eligible for Continued Risk Learning Credits.

Note: All courses come with a 90-day access to course materials and recordings on Qu.Academy from the activation/class-start date. You can extend access to Qu.Academy. Contact us for subscription options. All sales are final. No request for cancellations, exchanges, changes or refunds shall be honored.

Delivery

LIVE/ON DEMAND

Number of Modules

9 modules

Each module

1.5 hours/module

Registration options

ON DEMAND: Access now through Qu.Academy

Register

Machine Learning and AI for Financial Professionals Course - YouTube

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Machine Learning and AI for Financial Professionals Course QuantUniversity Channel

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MODULES

1: An intuitive Introduction to Machine Learning and AI

  • Machine Learning vs Statistics: How has the world changed?
  • A tour of Machine Learning and AI methods
    • Supervised Learning Vs Unsupervised Learning
    • Deep Learning
    • Reinforcement Learning
  • Key drivers influencing the adoption of Machine Learning and AI
    • Big Data, Hardware, Fintech, AI, Alternative Data
  • Key applications
    • Credit risk, Personalization, Predicting risk, Portfolio optimization and selection
  • Key players
    • Technology companies, Data vendors, Banks, Fintech startups

MODULES 2: Exploratory data analysis

  • Exploring and Visualizing large datasets
    • The Visualization zoo
    • A framework to decide how to chart datasets
    • Examples on how to build powerful dashboards
    • Case study 1: Visualizing Categorical, Numerical, Cross-sectional and Time series Financial datasets

MODULES 3: Unsupervised Learning

  • Dimension reduction and visualizing datasets using PCA, T-SNE
  • Manifold Learning
  • Case study: Visualizing high-dimensional Datasets

MODULES 4: Unsupervised Learning 2

  • Clustering Techniques
  • Distance measures
  • K-means
  • Hierarchical Clustering
  • Affinity Propagation
  • Case study 2: Using K-means for automatic clustering of stocks

MODULES 5: Supervised Learning

Learn from the past: How does Supervised machine learning work?

  • Cross sectional data
  • Time series analysis
  • Regression, Random Forests and Neural Networks
  • Evaluating machine learning algorithms
  • Case study 3: Predicting interest rates and credit risk using Alternative data sets.

MODULES 6: Neural Networks + Synthetic Data Generation

  • Introduction to Neural Networks and Deep Neural Networks
  • Case study 4: Synthetic Data Generation for VIX Scenarios

MODULES 7: Natural Language Processing

  • Making sense of Text and Natural Language Processing
  • Sentiment Analysis: How to interpret sentiments and use it in stock selection?
  • Case study 5: Analyzing Earning calls using text analytics

MODULES 8: Frontier topics

  • Key issues in adopting AI and Machine learning into investment workflows
  • How will Machine Learning and AI change the investment industry
  • Frontier topics
    • Anomaly detection
    • Reinforcement learning
    • Quantum Computing
    • Risk in Machine Learning and AI
    • Model governance, Interpretability and Model Management

MODULES 9: CAPSTONE PROJECT

Project presentations + Virtual Certificate Ceremony

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PAST ATTENDEES

Past Attendees of QuantUniversity workshops include Assette, Baruch College, Bentley College, Bloomberg, BNY Mellon, Boston University, Datacamp, Fidelity, Ford, Goldman Sachs, IBM, J.P. Morgan Chase, MathWorks, Matrix IFS, MIT Lincoln Labs, Morgan Stanley, Nataxis Global, Northeastern University, NYU, Pan Agora, Philips Health, Stevens Institute, T.D. Securities and many more..

PARTICIPANT FEEDBACK

Sri was an awesome instructor. He took care of the group's needs and offered different channels to pose questions.

Very competent and passionate about this very vast subject and caring about the learning of his students, even if the course was asynchronous - it has been real a pleasure to learn from Sri.

I really loved the format of this course. The flexibility with respect to time was great as the modules were prerecorded and the possibility to pose questions to the instructor in scheduled Q/A meetings was extremely useful.

KALIBA BILALA

CFA

I truly enjoyed your recent webinars with the CFA Institute and also learnt a lot. I look forward to more presentations from you.

Frederic Siboulet

Managing Director Ernst & Young Global Consulting Services

I loved the course. Very well organized, clear and concise delivery, with a lot of practical examples. Abundance of materials, with links to live examples, tools, websites, articles and books.

Michelle Allade

Director, Model Risk Management MetaBank

..Very good info and wish all the modules were unlocked so I could binge watch.

Comprehensive nature of the curriculum and the layout/sequence, which flowed very naturally. Along these lines, Sri did an effective job of introducing the big picture and alternating between focus on the building blocks and relating those back to the bigger picture.

Sri was an awesome instructor. He took care of the group's needs and offered different channels to pose questions.