Financial Analysis and Financial Modeling using MS Excel
- Offered byUDEMY
Financial Analysis and Financial Modeling using MS Excel at UDEMY Overview
Duration | 11 hours |
Total fee | ₹1,920 |
Mode of learning | Online |
Credential | Certificate |
Financial Analysis and Financial Modeling using MS Excel at UDEMY Highlights
- Earn Certificate of completion
- 30-Day Money-Back Guarantee
- Full lifetime access
- Step-by-step instructions on implementing Financial Analysis models in MS Excel
- With each lecture, there are class notes attached for you to follow along
Financial Analysis and Financial Modeling using MS Excel at UDEMY Course details
- Financial Analysts/ Managers who want to expand on the current set of skills or Anyone curious to master Excel for Financial Analysis in a short span of time
- Learn basics and advanced level Financial Accounting concepts that are required for Financial Analysis, specifically for job roles of Financial Analysts.
- Gain solid understanding on Financial Analysis and the role of Financial Analyst using MS Excel
- Make Finance Dashboards required for Financial Analysis and understand all the charts that you can draw in Excel
- Implement predictive ML models such as simple and multiple linear regression to predict outcomes to real-world financial problems
- Learn the commonly used financial formulas available in excel to calculate depreciation, loan-related calculations, NPV, IRR, etc., required for Financial Analysis
- Financial Analysis and Financial analytics provides scientific support to decision-making concerning a firm's money related matters.
- This course addresses the topic of Financial analysis with a practical focus, focusing especially on demystifying analytics for finance managers, financial analysts from both statistical and computing point of view.
Financial Analysis and Financial Modeling using MS Excel at UDEMY Curriculum
Essential MS Excel formulas and using them to calculate Financial metrics
In this part, we will start with a tutorial on all the popular MS Excel formulas.
Then we will see the implementation of these to calculate and automate the Financial metrics.
We also discuss a separate case study where we use Excel to calculate the average cost of external and internal hiring.
Visualization in Excel and Financial Dashboarding
In this part, we will begin with a tutorial on all the popular charts and graphs that can be drawn in MS Excel.
Then we will see the implementation of these to create visualize Financial data.
This is an important part of the course which help you grasp in-depth concepts of Financial Analysis in the later part of the course.
Data summarization using Pivot tables
In this part, we will learn about several advanced topics in MS Excel such as Pivot tables, indirect functions, and also about data formatting.
Then we will see the implementation of these to create beautiful summaries of Finance Data.
This is one of the building blocks of Financial Analysis and one of the major responsibilities of a Financial Analyst.
Basics of Machine Learning and Statistics
In this part, we introduce the students to the basics of statistics and ML, as nowadays Financial Analysis is getting integrated with these concepts.
This part is for students who have no background understanding of ML and statistics concepts.
Preprocessing Data for ML models
In this section, you will learn what actions you need to take step by step to get the data and then prepare it for analysis, these steps are very important.
We start with understanding the importance of business knowledge then we will see how to do data exploration.
We learn how to do uni-variate analysis and bivariate analysis then we cover topics like outlier treatment, missing value imputation, variable transformation, and correlation.
Linear regression model for predicting metrics
This section starts with a simple linear regression and then covers multiple linear regression.
We have covered the basic theory behind each concept without getting too mathematical about it so that you understand where the concept is coming from and how it is important.