Get updates on Eligibility, Admission, Placements Fees Structure
Quick Facts
| Medium Of Instructions | Mode Of Learning | Mode Of Delivery |
|---|---|---|
| English | Self Study | Video and Text Based |
Course Overview
The Using Machine Learning in Trading and Finance online course is providing a platform for the students to learn and study about the basics that are involved in developing advanced strategies that are used in modern machine learning techniques.
In the online programme on Using Machine Learning in Trading and Finance by Coursera, the applicants will be studying the key components that are common to all the trading strategies irrespective of the platforms and dimensions.
In the Using Machine Learning in Trading and Finance certification syllabus, the enrolled students will be covering the comprehensive chapters of- Regularization: L1, L2, and early stopping, Regularization: dropout, Lab Intro: Keras functional API, Regularization: the basics, Neural networks with Keras functional API, Collect the data, Backtest on unseen data, Selecting a machine learning algorithm, Lab Intro: momentum trading, Creating features, Define the problem, Split the data and others.
The Highlights
- 100% online programme
- Shareable certificate
- Deadlines flexible
- Course level intermediate
- Programme by Coursera
- Course offered by New York Institute of Finance and Google cloud
- 18 hours total course duration
- Subtitles in English
Programme Offerings
- Online Course
- video lectures
- Practice Sets
- assignments
- quizzes
- case study.
Courses and Certificate Fees
| Certificate Availability | Certificate Providing Authority |
|---|---|
| yes | Coursera |
The fees for the course Using Machine Learning in Trading and Finance is -
| Head | Amount in INR |
| 1 month | Rs. 4,115 |
| 3 month | Rs. 8,230 |
| 6 month | Rs. 12,345 |
Eligibility Criteria
Work Experience
The candidates must have a working knowledge of SQL to apply and enrol for this programme.
Education
To apply for the Using Machine Learning in Trading and Finance certification course, the students need to have advanced competency in the domain of Python programming and familiarity with pertinent libraries for machine learning - StatsModels, Pandas and Scikit-Learn. The student also needs to have a background in statistics (linear regressions, probability, higher moments, Gaussian distributions, standard deviation, expected values) and financial markets( hedging, market structure, derivatives, bonds, equities).
Certification Qualification Details
Students will be getting the Using Machine Learning in Trading and Finance certification after they successfully complete the course in the stipulated time frame. They are also required to make a fee payment to pursue the programme once the 7 days free trial period ends.
What you will learn
The Using Machine Learning in Trading and Finance programme will give detailed insight about the following elements to the students:
- The candidates will get a detailed understanding of the subject of Tensorflow.
- The topic of the TensorFlow API hierarchy will be studied by the students in the course.
- Applicants will be studying the process of Working in memory and its application.
- The Using Machine Learning in Trading and Finance certification syllabus includes the chapter on activation functions
- The process of Picking pairs with clustering is also included in the course.
- The detailed dynamics and process of Google Cloud will be taught to the candidates.
- The Components of TensorFlow tensors will be taught to the students.
- Applicants will be taught about neural methods of programming.
- Learners will study Keras functional AP
- The process of collecting data is also included in the programme module.
Who it is for
The Using Machine Learning in Trading and Finance programme is for the following students-
- Candidates who want to study Kalman filters can apply for the course directly.
Application Details
To apply for the Using Machine Learning in Trading and Finance online programme the students have to follow the given steps-
Step 1: The students have to visit the following website- https://www.coursera.org/learn/machine-learning-trading-finance
Step 2: The students have to click on the “enrol” button.
Step 3: The students then fill in the credentials that are mentioned in the form.
Step 4: The course fee needs to be deposited for accessing the course materials.
The Syllabus
Videos
- Introduction to Course
- Basic Trading Strategy Entries and Exits Endogenous Exogenous
- Basic Trading Strategy Building a Trading Model
- Advanced Concepts in Trading Strategies
Reading
- Welcome to Using Machine Learning in Trading and Finance
Quiz
- Understand Quantitative Strategies
Videos
- Overview
- Introduction to TensorFlow
- TensorFlow API Hierarchy
- Components of TensorFlow Tensors and Variables
- Getting Started with Google Cloud Platform and Qwiklabs
- Lab Intro Writing low-level TensorFlow programs
- Working in-memory and with files
- Training on Large Datasets with tf.data API
- Getting the data ready for model training
- Embeddings
- Lab Intro Manipulating data with TensorFlow Dataset API
App items
- Lab: Writing low-level TensorFlow Programs
- Lab: Manipulating data with TensorFlow Dataset API
Videos
- Overview
- Activation functions
- Activation functions: Pitfalls to avoid in Backpropagation
- Neural Networks with Keras Sequential API
- Serving models in the cloud
- Lab Intro : Keras Sequential API
- Neural Networks with Keras Functional API
- Regularization: The Basics
- Regularization: L1, L2, and Early Stopping
- Regularization: Dropout
- Lab Intro: Keras Functional API
- Recap
App items
- Lab: Introducing the Keras Sequential API
- Lab: Introducing the Keras Functional API
Videos
- Introduction to Momentum Trading
- Introduction to Hurst
- Building a Momentum Trading Model
- Define the Problem
- Collect the Data
- Creating Features
- Split the Data
- Selecting a Machine Learning Algorithm
- Backtest on Unseen Data
- Understanding the Code: Simple ML Strategies to Generate Trading Signal
- Lab Intro: Momentum Trading
- Momentum Trading Lab Solution
Reading
- Hurst Exponent and Trading Signals Derived from Market Time Series
App items
- Lab: Momentum Strategies
- Optional Lab: Improve Momentum Trading strategies using Hurst
Discussion Prompt
- Compare interpretability versus explanatory power of the momentum factor
Videos
- Introduction to pair trading
- Picking pairs
- Picking pairs with clustering
- How to implement a pair trading strategy
- Evaluate results of a pair trade
- Backtesting and avoiding overfitting
- Next steps: improvements to your pair strategy
- Lab intro: pairs trading
- Lab solution: pairs trading
- Kalman filter introduction
- Kalman filter trading applications
Quiz
- Pairs Trading Strategy concepts
App items
- Lab: Pairs Trading Strategy
- Optional Lab: Estimate parameters using Kalman Filters
Instructors
New York Institute of Finance, New York Frequently Asked Questions (FAQ's)
Yes, in the course of Using Machine Learning in Trading and Finance training the students will be provided with scholarship aids.
The programme does not have any mandated registration fee. The registration for the course is free.
Yes, for the ease of the students understanding, the course has the provision of English subtitles.
No, for the Using Machine Learning in Trading and Finance certification there is no specified eligibility.
The students will get to access the course guides once they enrol for the Using Machine Learning in Trading and Finance programme.
For applying for the course, the following link has to be visited- https://www.coursera.org/learn/machine-learning-trading-finance
Yes, the Using Machine Learning in Trading and Finance online course is having a shareable certificate.
Yes, for a period of 7 days, the students will get to access the free trial.
Yes, the Using Machine Learning in Trading and Finance certification benefits the students by allowing them to access the course in the self-paced learning mode.