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PG Diploma in Indian and Foreign Accounting Course (PGDIFA)

Enhance your skills with our PGDIFA course. Learn to manage financial accounting, analyze reports, and navigate key financial processes to advance your career in the accounting and finance industry. Students enrolled in the PG Diploma in Indian and Foreign Accounting (PGDIFA) program learn advanced accounting techniques for domestic and international companies. This diploma in Indian and foreign accounting course has the potential to lead to high salary packages and international work prospects. Since this is a job-oriented course, students will benefit from placement assistance and several internship opportunities. 

Offline Fees

Starts at Rs. 79650

Online Fees

Starts at Rs. 57525

Duration

9 Months

Download Syllabus
Apply Now
  • Finance
  • Cloud Accounting
  • Online & Offline
  • Malayalam, English
  • Hurry! 665 people have already applied in the last 1 month
  • For enquiries call: Get Started
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Choose Your Perfect Course

Advanced Generative AI Certification Course

Master the skills that shape the future of technology with the Advanced Certificate Program in Generative AI, a 5-month generative AI course by upGrad.

No Cost EMI

Starts at Rs. 6,458

Start Date

Starts at Rs. 6,458

Duration

4 Months

Download Syllabus
Apply Now
  • Hurry! 665 people have already applied in the last 1 month
  • For enquiries call: Get Started

Introduction to PG Diploma in Indian and Foreign Accounting Course(PGDIFA)

Course Snapshot

Hours of Learning
0 +
Industry Projects
0 +
Accounting Tools
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Finprov’s nine-month diploma in Indian and foreign accounting (PGDIFA) course provides students with the fundamental knowledge and abilities required for positions in accounting and finance. This course is your gateway to mastering financial expertise and unlocking global career opportunities. There would be personalized mentorship sessions throughout the course. Students can also solve doubts with expert mentors. The course covers worldwide accounting standards, payroll, TDS, and GST.

  • Up-to-date Generative AI modules
  • Learn 10+ Generative AI tools, including a ChatGPT course
  • Upskill through real projects
  • Gen AI masterclasses by industry experts
  • upGrad Alumni Status
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Comprehensive Curriculum

A complete program designed to help you master finance and accounting, giving you the skills to stay ahead in the industry.

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Key Highlights of PGDIFA Course

What does this course have to offer?

Our curriculum covers in-demand industry relevant topics

  • Financial Accounting
  • Cost Accounting
  • Taxation
  • Invoice Management
  • Expense Monitoring
  • Auditing Principles
  • Financial Reporting
  • Budgeting and Forecasting
  • Banking and Financial Services

PGDIFA will help you improve your accounting skills by teaching you how to manage invoices and expenses more efficiently. 

  • Small and Medium Business Owners
  • Accountants and Bookkeepers
  • ChatGPT
  • Finance Managers
  • Freelancers and Consultants
  • Entrepreneurs
  • Startups
  • Non-profit Organizations

PGDIFA provides superior financial management skills, allowing you to track bills, costs, and financial records accurately for better decision-making.

  • Financial Analyst
  • Payroll Specialist
  • Tax Consultant
  • Finance Manager
  • Accounts Receivable/Payable Specialist
  • Billing Specialist
  • Budget Analyst
  • Auditor
  • Cost Accountant

The PGDIFA program provides the necessary industry skills to prepare for various positions in accounting, finance, payroll management, and taxation.

  • Generative AI Models
  • Transformers
  • ChatGPT
  • Prompt Engineering
  • Product Development
  • Product Development
  • Deploy Web Apps with Flask

Students must have completed any degree from a recognized university to enroll in this course.

Master PGDIFA today!

Gain expertise in finance and accounting, get certified and build the skills needed to advance your career in the industry.

Download Syllabus

Earn Valuable Credentials And Recognition

Make your resume stand out with an Advanced Certification in Tally Prime and boost your accounting career.

WhatsApp Image 2025 01 10 at 15.32.20 1

Key Highlights of PGDIFA Course

Earn valuable Credentials And Recognition

Enhance your career with the PGDIFA course and develop essential skills for success in the finance and accounting sector. Gain expertise in key financial processes to boost your job prospects and stand out in the industry.

WhatsApp Image 2025-01-10 at 15.32.20
WhatsApp Image 2025-01-10 at 15.32.20

Courses

Meet Our Expert Team

Meet the experts who will guide you through your learning journey and help you reach your career goals

Ashna 3

CA Ashna Bharath Pillai

Chief Financial Officer

Veena 5

CA Veena Vijayan

Chief Operational Officer

Anish 1

CA Anish Thomas

Academic Head - Karnataka

Tanya 1

CA Taniya Mathew

Academic Head - Kerala

World-Class Curriculum

Master PGDIFA with a World-Class Curriculum

Learn PGDIFA with expert guidance, build practical skills, and confidently advance your career. Gain hands-on experience and master data-driven decision-making.

Download Syllabus

Duration : 7 Weeks

Machine Learning I:

This introductory course explores the foundational machine learning concepts, starting with Linear Regression and its practical applications. It then covers Logistic Regression and Naive Bayes, highlighting their use in classification tasks. Finally, the course covers model selection techniques to ensure the best performance of machine learning models in various scenarios.

Topics Covered:

  • Linear Regression
  • Linear Regression Assignment
  • Logistic Regression
  • Naive Bayes
  • Model Selection
  • Linear Regression
  • Linear Regression Assignment
  • Logistic Regression
  • Naive Bayes
  • Model Selection

Duration : 7 Weeks

Machine Learning I:

This introductory course explores the foundational machine learning concepts, starting with Linear Regression and its practical applications. It then covers Logistic Regression and Naive Bayes, highlighting their use in classification tasks. Finally, the course covers model selection techniques to ensure the best performance of machine learning models in various scenarios.

Topics Covered:

  • Linear Regression
  • Linear Regression Assignment
  • Logistic Regression
  • Naive Bayes
  • Model Selection
  • Linear Regression
  • Linear Regression Assignment
  • Logistic Regression
  • Naive Bayes
  • Model Selection

Duration : 7 Weeks

Machine Learning I:

This introductory course explores the foundational machine learning concepts, starting with Linear Regression and its practical applications. It then covers Logistic Regression and Naive Bayes, highlighting their use in classification tasks. Finally, the course covers model selection techniques to ensure the best performance of machine learning models in various scenarios.

Topics Covered:

  • Linear Regression
  • Linear Regression Assignment
  • Logistic Regression
  • Naive Bayes
  • Model Selection
  • Linear Regression
  • Linear Regression Assignment
  • Logistic Regression
  • Naive Bayes
  • Model Selection

Duration : 7 Weeks

Machine Learning I:

This introductory course explores the foundational machine learning concepts, starting with Linear Regression and its practical applications. It then covers Logistic Regression and Naive Bayes, highlighting their use in classification tasks. Finally, the course covers model selection techniques to ensure the best performance of machine learning models in various scenarios.

Topics Covered:

  • Linear Regression
  • Linear Regression Assignment
  • Logistic Regression
  • Naive Bayes
  • Model Selection
  • Linear Regression
  • Linear Regression Assignment
  • Logistic Regression
  • Naive Bayes
  • Model Selection

Duration : 7 Weeks

Machine Learning I:

This introductory course explores the foundational machine learning concepts, starting with Linear Regression and its practical applications. It then covers Logistic Regression and Naive Bayes, highlighting their use in classification tasks. Finally, the course covers model selection techniques to ensure the best performance of machine learning models in various scenarios.

Topics Covered:

  • Linear Regression
  • Linear Regression Assignment
  • Logistic Regression
  • Naive Bayes
  • Model Selection
  • Linear Regression
  • Linear Regression Assignment
  • Logistic Regression
  • Naive Bayes
  • Model Selection

Duration : 7 Weeks

Machine Learning I:

This introductory course explores the foundational machine learning concepts, starting with Linear Regression and its practical applications. It then covers Logistic Regression and Naive Bayes, highlighting their use in classification tasks. Finally, the course covers model selection techniques to ensure the best performance of machine learning models in various scenarios.

Topics Covered:

  • Linear Regression
  • Linear Regression Assignment
  • Logistic Regression
  • Naive Bayes
  • Model Selection
  • Linear Regression
  • Linear Regression Assignment
  • Logistic Regression
  • Naive Bayes
  • Model Selection

Duration : 7 Weeks

Machine Learning I:

This introductory course explores the foundational machine learning concepts, starting with Linear Regression and its practical applications. It then covers Logistic Regression and Naive Bayes, highlighting their use in classification tasks. Finally, the course covers model selection techniques to ensure the best performance of machine learning models in various scenarios.

Topics Covered:

  • Linear Regression
  • Linear Regression Assignment
  • Logistic Regression
  • Naive Bayes
  • Model Selection
  • Linear Regression
  • Linear Regression Assignment
  • Logistic Regression
  • Naive Bayes
  • Model Selection

Duration : 7 Weeks

Machine Learning I:

This introductory course explores the foundational machine learning concepts, starting with Linear Regression and its practical applications. It then covers Logistic Regression and Naive Bayes, highlighting their use in classification tasks. Finally, the course covers model selection techniques to ensure the best performance of machine learning models in various scenarios.

Topics Covered:

  • Linear Regression
  • Linear Regression Assignment
  • Logistic Regression
  • Naive Bayes
  • Model Selection
  • Linear Regression
  • Linear Regression Assignment
  • Logistic Regression
  • Naive Bayes
  • Model Selection

What you'll learn

  • Explain what Data Analytics is and the key steps in the Data Analytics process
  • Differentiate between different data roles such as Data Engineer, Data Analyst, Data Scientist, Business Analyst, and Business Intelligence Analyst
  • Describe the different types of data structures, file formats, and sources of data
  • Describe the data analysis process involving collecting, wrangling, mining, and visualizing data

Skills you'll gain

  • Model Selection
  • Data Analysis
  • Python Programming
  • Data Visualization
  • Predictive Modelling

What you'll learn

  • Explain what Data Analytics is and the key steps in the Data Analytics process
  • Differentiate between different data roles such as Data Engineer, Data Analyst, Data Scientist, Business Analyst, and Business Intelligence Analyst
  • Describe the different types of data structures, file formats, and sources of data
  • Describe the data analysis process involving collecting, wrangling, mining, and visualizing data

Skills you'll gain

  • Model Selection
  • Data Analysis
  • Python Programming
  • Data Visualization
  • Predictive Modelling

What you'll learn

  • Explain what Data Analytics is and the key steps in the Data Analytics process
  • Differentiate between different data roles such as Data Engineer, Data Analyst, Data Scientist, Business Analyst, and Business Intelligence Analyst
  • Describe the different types of data structures, file formats, and sources of data
  • Describe the data analysis process involving collecting, wrangling, mining, and visualizing data

Skills you'll gain

  • Model Selection
  • Data Analysis
  • Python Programming
  • Data Visualization
  • Predictive Modelling

What you'll learn

  • Explain what Data Analytics is and the key steps in the Data Analytics process
  • Differentiate between different data roles such as Data Engineer, Data Analyst, Data Scientist, Business Analyst, and Business Intelligence Analyst
  • Describe the different types of data structures, file formats, and sources of data
  • Describe the data analysis process involving collecting, wrangling, mining, and visualizing data

Skills you'll gain

  • Model Selection
  • Data Analysis
  • Python Programming
  • Data Visualization
  • Predictive Modelling

What you'll learn

  • Explain what Data Analytics is and the key steps in the Data Analytics process
  • Differentiate between different data roles such as Data Engineer, Data Analyst, Data Scientist, Business Analyst, and Business Intelligence Analyst
  • Describe the different types of data structures, file formats, and sources of data
  • Describe the data analysis process involving collecting, wrangling, mining, and visualizing data

Skills you'll gain

  • Model Selection
  • Data Analysis
  • Python Programming
  • Data Visualization
  • Predictive Modelling

What you'll learn

  • Explain what Data Analytics is and the key steps in the Data Analytics process
  • Differentiate between different data roles such as Data Engineer, Data Analyst, Data Scientist, Business Analyst, and Business Intelligence Analyst
  • Describe the different types of data structures, file formats, and sources of data
  • Describe the data analysis process involving collecting, wrangling, mining, and visualizing data

Skills you'll gain

  • Model Selection
  • Data Analysis
  • Python Programming
  • Data Visualization
  • Predictive Modelling

What you'll learn

  • Explain what Data Analytics is and the key steps in the Data Analytics process
  • Differentiate between different data roles such as Data Engineer, Data Analyst, Data Scientist, Business Analyst, and Business Intelligence Analyst
  • Describe the different types of data structures, file formats, and sources of data
  • Describe the data analysis process involving collecting, wrangling, mining, and visualizing data

Skills you'll gain

  • Model Selection
  • Data Analysis
  • Python Programming
  • Data Visualization
  • Predictive Modelling

What you'll learn

  • Explain what Data Analytics is and the key steps in the Data Analytics process
  • Differentiate between different data roles such as Data Engineer, Data Analyst, Data Scientist, Business Analyst, and Business Intelligence Analyst
  • Describe the different types of data structures, file formats, and sources of data
  • Describe the data analysis process involving collecting, wrangling, mining, and visualizing data

Skills you'll gain

  • Model Selection
  • Data Analysis
  • Python Programming
  • Data Visualization
  • Predictive Modelling

What you'll learn

  • Explain what Data Analytics is and the key steps in the Data Analytics process
  • Differentiate between different data roles such as Data Engineer, Data Analyst, Data Scientist, Business Analyst, and Business Intelligence Analyst
  • Describe the different types of data structures, file formats, and sources of data
  • Describe the data analysis process involving collecting, wrangling, mining, and visualizing data

Skills you'll gain

  • Model Selection
  • Data Analysis
  • Python Programming
  • Data Visualization
  • Predictive Modelling

What you'll learn

  • Explain what Data Analytics is and the key steps in the Data Analytics process
  • Differentiate between different data roles such as Data Engineer, Data Analyst, Data Scientist, Business Analyst, and Business Intelligence Analyst
  • Describe the different types of data structures, file formats, and sources of data
  • Describe the data analysis process involving collecting, wrangling, mining, and visualizing data

Skills you'll gain

  • Model Selection
  • Data Analysis
  • Python Programming
  • Data Visualization
  • Predictive Modelling

What you'll learn

  • Explain what Data Analytics is and the key steps in the Data Analytics process
  • Differentiate between different data roles such as Data Engineer, Data Analyst, Data Scientist, Business Analyst, and Business Intelligence Analyst
  • Describe the different types of data structures, file formats, and sources of data
  • Describe the data analysis process involving collecting, wrangling, mining, and visualizing data

Skills you'll gain

  • Model Selection
  • Data Analysis
  • Python Programming
  • Data Visualization
  • Predictive Modelling

What you'll learn

  • Explain what Data Analytics is and the key steps in the Data Analytics process
  • Differentiate between different data roles such as Data Engineer, Data Analyst, Data Scientist, Business Analyst, and Business Intelligence Analyst
  • Describe the different types of data structures, file formats, and sources of data
  • Describe the data analysis process involving collecting, wrangling, mining, and visualizing data

Skills you'll gain

  • Model Selection
  • Data Analysis
  • Python Programming
  • Data Visualization
  • Predictive Modelling

What you'll learn

  • Explain what Data Analytics is and the key steps in the Data Analytics process
  • Differentiate between different data roles such as Data Engineer, Data Analyst, Data Scientist, Business Analyst, and Business Intelligence Analyst
  • Describe the different types of data structures, file formats, and sources of data
  • Describe the data analysis process involving collecting, wrangling, mining, and visualizing data

Skills you'll gain

  • Model Selection
  • Data Analysis
  • Python Programming
  • Data Visualization
  • Predictive Modelling

What you'll learn

  • Explain what Data Analytics is and the key steps in the Data Analytics process
  • Differentiate between different data roles such as Data Engineer, Data Analyst, Data Scientist, Business Analyst, and Business Intelligence Analyst
  • Describe the different types of data structures, file formats, and sources of data
  • Describe the data analysis process involving collecting, wrangling, mining, and visualizing data

Skills you'll gain

  • Model Selection
  • Data Analysis
  • Python Programming
  • Data Visualization
  • Predictive Modelling

Instructors

Group 1722

IBM Skills Network Team

IBM
58 Courses • 1,041,505 learners

Group 1722

IBM Skills Network Team

IBM
58 Courses • 1,041,505 learners

PGDIFA Course Highlights

Skills You Will Acquire

GST

Income Tax

SAP FICO

Auditing

Invoice

Corporate Tax

TDS

PGDIFA Course Career Outcomes

What our learners have achieved?

A quick summary of the placement support received by this program’s alumni

32%

Avg. Salary Hike

86%

Learners Achieving their Outcomes

3500+

Successful Transitions

250+

Hiring Partners

Top Recruiters

Group 1171274777
Group 1171274778
Group 1171274779
Group 1171274780

PGDIFA Course Eligibility & Admissions

How To Apply

The application journey is simple and straightforward, and can be completed in three easy steps.

Apply Now

Fill the Application Form

Fill out the application form on the upGrad portal

Get Shortlisted

You will receive a shortlisting email based on your profile

Block Your Seat

Secure your seat by paying the course fee

Industry Experts - PGDIFA

Learn from Industry Leaders And Experts

Transform your career and become a PGDIFA Expert today!

Gain hands-on experience and industry knowledge to build a successful career in the accounting sector. Learn from experts and step into a high-demand field.

Download Syllabus

FAQ

Frequently Asked Questions

The application journey is simple and straightforward, and can be completed in three easy steps.

What is the duration of the PGDIFA course?
Depending on your chosen institution, the course typically takes 9 months.

Yes. Upon completing the course, you will obtain a PG diploma certificate, which will help you excel in your accounting career.

Yes. The course will teach you about Payroll Management and other accounting concepts in detail.

PGDIFA focuses more on financial analysis and investment strategies, while an MBA covers core management topics.

Yes, Every student will get practical exposure to AI-integrated accounting tools.




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