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1) Learn the basics of Financial markets and instruments.
2) Learn to use Python language for Financial Analysis
3) Master Excel for Financial Data analysis and Visualization.
4) Apply Data Analysis techniques to real-world Financial Data
5) Create reports and visualizations using Python and Excel
Financial Data Analytics
Need for Financial Data Analytics
This course covers the integration of financial concepts and Python programming with Excel, enabling students to analyze and visualize financial data more efficiently. Students will learn to use Python libraries such as pandas, NumPy, and matplotlib to work with financial data, and to create visualizations and reports using Excel.
Financial data analytics is crucial in today’s business environment as it enables organizations to make informed decisions based on data-driven insights. It helps in analyzing large volumes of financial data, identifying trends, assessing risks, and predicting future market movements. By leveraging tools and techniques such as statistical analysis, machine learning, and predictive modeling, financial data analytics improves operational efficiency, optimizes investment strategies, and enhances risk management. Additionally, it enables real-time monitoring of financial performance, ensuring better compliance with regulatory requirements and supporting strategic growth initiatives. Ultimately, it empowers businesses to gain a competitive edge in a rapidly evolving financial landscape.
What does this Course Offer ?
- Complimentary Python Programming Bootcamp
- Designed for Working Professionals and Students
- 20+ Case Studies and 5+ Industry Projects
- Dedicated Student Support
- Exclusive Job Assistance
- Live coding classes and profile building workshops
- Programming – Python
- Advance Excel with VBA
- Data Manipulation & Analysis – Data Wrangling , Data Visualization , Exploratory Data Analysis (EDA):
- Opportunity to wok on live-projects as part of Internship on reputed Companies.
- Internship work certificate
- Certification on Python from IIT Bombay
- Certification on Financial Data Analytics from Central Govt. of India
Both the below mode of Training is available.
Online Mode – Live Class
Offline Mode
- Overview of financial markets and instruments (stocks, bonds, derivatives, etc.)
- Introduction to financial data analysis and visualization
- Introduction to Python programming language
- Basic syntax and data types in Python
- Variables, operators, control structures, and functions in Python
- Introduction to NumPy and pandas’ libraries
- Reading and writing CSV files with pandas
- Data manipulation and cleaning with pandas
- Data visualization with matplotlib
- Basic statistical analysis with pandas
- Introduction to Excel programming with VBA
- Creating macros and automating tasks in Excel
- Working with Excel formulas and functions
- Using Excel for financial data analysis (charts, tables, etc.)
- Creating custom reports and dashboards in Excel
- Using Excel’s built-in functions for financial analysis (e.g. XNPV, XIRR)
- Using regression analysis with Python and Excel
- Using Monte Carlo simulations with Python
- Advanced data visualization techniques with matplotlib and Seaborn
Introduction Tableau , Connecting to Excel, CSV Text Files , Connecting to Databases , Working with Data , Analyzing , Formatting , Introduction to Calculations , Dashboard Development, Data Calculations , Aggregate Calculations , User Calculations ,Table Calculations , Logical Calculations , String Calculations , Number Calculations , iterating Conditions , Filtering Measures , Histograms , Sorting , Grouping , Tree maps, word clouds and Different Charts.
- Students will work on a project that applies the concepts learned in the course to a real-world financial problem or dataset
- Students will create a report and presentation using Python and Excel
Quick Contact Form
Eligibility Criteria
- Graduates or Colleges Students from any discipline
- No prior work experience required
- No prior coding experience or tech know-how required
Best Suited For
- IT Professionals
- Marketing Professionals
- Recent Graduates
Financial Analytics FAQs
Financial analytics or finance analytics refers to the tools and processes used to observe datasets and get insights into an organization’s financial performance. It provides valuable details about an organization’s financial data that helps make strategic decisions to improve its overall performance. When it comes to enterprise performance management and business intelligence, financial analytics significantly influences all aspects of the business. It plays an important role in the evaluation of profits, answering business-related queries, and future business forecasting.
Financial analytics provides meaningful analysis of a company’s financial report that helps its shareholders, stakeholders, and management make appropriate decisions. This is done by combining internal financial data with external data from social media, demographics, and big data sources. It shapes business strategy through reliable and factual insight rather than intuition.
You must meet the following requirements to be admitted to the Data Science and ML Course :
- A bachelor’s degree/ Class 12 passed with a grade point average of at least 50%.
- Understanding the fundamentals of coding and Accounts.
- Client Profitability Analytics distinguishes between clients who generate revenue for a company and those who do not.
- Product Profitability Analytics refers to evaluating each product individually rather than determining overall profitability at a company.
- Cash-flow Analytics predicts cash flow using the working capital ratio and cash conversion cycle.
- Predictive Sales Analytics include forecasting sales using correlation analysis or past trends.
- Fraud Detection and Prevention
Financial institutions use machine learning tools to identify unusual consumer behaviors. This helps banks respond quickly to reduce losses for both businesses and consumers. For example, with the rise of cybercrime, many banks have implemented algorithms to detect fraudsters from their unusual activities and put an end to their activity. - Predictive Analytics and Planning
The algorithms of predictive analytics use various data, such as customers’ past payment records, current financial strength, market conditions, and so on, to predict whether a customer will pay on time or not. This type of data helps the companies identify doubtful debts and debtors so they can mark their books accordingly. - Staying Competitive
The technological revolution is affecting every business and motivating them to outperform the competition. Financial analytics tools are versatile, automated, and can be integrated easily with existing systems. Business users can improve their efficiency and focus on the core task that requires cognitive skills.
The scope of a financial reporting analyst’s work is wide-ranging and involves working with a variety of financial data, including budgets, forecast models, and financial ratios. They may also be responsible for monitoring and analyzing market trends in order to inform business decisions
Critical technical skills you will need when working in financial analytics include a range of accounting skills, such as bookkeeping, technical analysis, forecasting, and budgeting. Software and tools like Excel and other spreadsheets are also critical in record keeping and analysis. You may use various skills depending on where you work and the individual or organization’s goals. More specific technical skills include:
Valuation analysis
Joint venture analysis
Internal rate of return
Return on investment capital
Year over year
Net present value
Financial modeling
Corporate finance
Mergers and acquisition analysis
Leveraged buyout method
Reading SEC filings
- Strong quantitative skills
- Strong analytical skills
- Strong computer skills
- Good presentation skills
- Good decision-making ability
- Problem-solving ability
- Adeptness in the use of logic
- Detail oriented
- Decent communication skills