| Attribute | Detail |
|---|---|
| Format | Online, self-paced course |
| Level | Beginner |
| Duration | 2–3 Weeks |
| Certification | e-Certification |
| Fee | ₹199 / $20 |
| Tools | Machine Learning Financial Data Predictive Analytics Risk Analysis Data Trends |
About the Machine Learning in Finance: Basics Course
The Machine Learning in Finance: Basics course is a free, beginner-friendly self-paced program designed to introduce learners to how machine learning is applied in the financial domain.
The course explains how data-driven models are used to analyze financial data, predict trends, manage risk, and support decision-making in areas like banking, investment, and financial services. Learners will explore basic concepts such as financial data, prediction models, and simple machine learning applications in finance. This course is ideal for beginners who want to understand the intersection of AI and finance.
Program Highlights
• Free beginner-level ML in finance course
• Online self-paced learning format
• Simple explanation of finance and ML concepts
• Covers prediction, risk analysis, and financial data basics
• Real-world examples from banking and investment
• Suitable for students and first-time learners
• e-Certification upon successful completion
Course Curriculum
Module 1: Introduction to Machine Learning in Finance
- What is Machine Learning in Finance?
- Role of Data in Financial Systems
- Applications of ML in Banking and Investment
- Overview of Financial Decision-Making
Module 2: Understanding Financial Data
- Types of Financial Data: Market, Transactions, and Time Series
- Introduction to Stock, Price, and Market Trends
- Features and Variables in Financial Analysis
- Importance of Data Quality
Module 3: Basic ML Applications in Finance
- Predicting Prices and Trends
- Credit Scoring and Risk Assessment
- Fraud Detection Concepts
- Customer Analytics in Financial Services
Module 4: Model Evaluation and Risk Basics
- Understanding Prediction Accuracy
- Risk and Uncertainty in Financial Models
- Overfitting and Reliability Basics
- Interpreting Model Results in Finance
Module 5: Applications and Future Scope
- AI in Investment, Trading, and Banking
- Role of ML in FinTech and Digital Finance
- Career Opportunities in AI and Finance
- Mini Learning Activity / Concept-Based Practice
Tools, Techniques, or Platforms Covered
Machine Learning Financial Data Predictive Analytics Risk Analysis Data Trends
Real-World Applications
- Predicting stock price trends and market behavior
- Detecting fraud in banking and financial transactions
- Assessing credit risk and loan approvals
- Analyzing customer behavior in financial services
- Supporting decision-making in investment and trading
Who Should Attend & Prerequisites
- This course is suitable for students, beginners, freshers, and professionals interested in understanding how machine learning is applied in finance.
- It is also useful for learners from finance, commerce, management, economics, engineering, and data-related fields.
Certification
