Get updates on Eligibility, Admission, Placements Fees Structure
Quick Facts
| Medium Of Instructions | Mode Of Learning | Mode Of Delivery |
|---|---|---|
| English | Self Study, Virtual Classroom | Video and Text Based |
Course Overview
The Financial Analytics: Forecasting, Modeling, and Optimization Training Course is a 6-week long course that discusses fundamental aspects of data analytics and its applications in the financial sector. The course will explore the role of financial management strategies in the modern industrial world.
Through the Financial Analytics: Forecasting, Modeling, and Optimization Certification Course, learners will be introduced to the core principles of data analytics and data-driven decision-making skills. The online course will be covered in 6 modules taught by experts at The Wharton School.
After successful completion of the Financial Analytics: Forecasting, Modeling, and Optimization Online Course, learners will receive a digital certificate of completion from the Wharton School.
The Highlights
- Certificate of completion
- 6 weeks duration
- 4 to 6 hours weekly study
- Video lectures
- Activities and assignments
- Expert faculty
Programme Offerings
- Certificate of completion
- 6 Weeks Duration
- 4 to 6 Weekly Study Hours
- video lectures
- Activities and Assignments
Courses and Certificate Fees
| Certificate Availability | Certificate Providing Authority |
|---|---|
| yes | The Wharton School, Philadelphia |
The Financial Analytics: Forecasting, Modeling, and Optimization Course fee are US$2,600. Flexible payment options are available where you can pay the fees in installments. There is a special group enrollment pricing offer up to a 20% discount if you enroll with your colleagues.
Financial Analytics: Forecasting, Modeling, and Optimization Course Fee Structure
Course | Amount in USD |
Financial Analytics: Forecasting, Modeling, and Optimization | US$2,600 |
What you will learn
After completing the Financial Analytics: Forecasting, Modeling, and Optimization Classes, you will learn about the following topics:
- Data analytics for financial decisions
- Data science workflow
- Financial data analysis
- Exploratory data analysis
- Application of forecasting techniques
- Interpretation of credit risk models
- Investment portfolios
- Data analytics solutions
Who it is for
- The course is suitable for anyone interested in data analytics, financial analytics, or data science.
- The course can be opted by anyone wishing to take up career roles like financial analysts or financial advisors.
Admission Details
Given below are the steps to enroll in the Financial Analytics: Forecasting, Modeling, and Optimization Training Course:
Step 1: Go to the official website by clicking on the URL given below -https://online-execed.wharton.upenn.edu/financial-analytics
Step 2: Click on the 'Apply Now' option at the end of the page.
Step 3: Create an account and register to continue.
The Syllabus
- Understand the value of data analytics when making financial decisions
- Create an outline of the data science workflow
- Learn potential pitfalls of data analytics
- Determine goals for financial data analysis
- Perform exploratory data analysis
- Formulate and refine relevant questions based on available data
- Gain insights into data patterns
- Gain insights into the role of modeling in shaping market expectations
- Apply forecasting techniques to business decisions
- Choose an appropriate modeling technique for the desired outcome
- Interpret machine-learning output
- Define credit risk
- Analyze financial statements for credit risk
- Identify credit key performance indicators (KPIs)
- Interpret credit risk models
- Define investment portfolios
- Identify various asset classes
- Construct optimal portfolios, using a variety of methods, strategies, and tools
- Specify the challenge you wish to solve at your organization by using data analytics
- Propose a data analytics solution
- Identify potential pitfalls and problems
- Select appropriate methods to visualize and present data
- Justify the choice of modeling techniques for real-world problem solving
- Analyze internal and external resource needs for team building
- Produce an action plan that prioritizes results and identifies key deliverables