This course provides a solid foundation in financial accounting, manual bookkeeping, and GST fundamentals. Through a mix of theory, hands-on practice, and real-life transaction examples, learners will develop job-ready skills for various roles in the accounting field.

• Students (10+2 pass or pursuing graduation – preferably in Commerce, Arts, or related streams)
• Fresh Graduates looking for entry-level accounting or office jobs
• Job Seekers interested in roles like Accounts Assistant, Office Executive, or Billing Clerk
• Entrepreneurs & Small Business Owners who want to manage their finances better
• Professionals from non-commerce backgrounds who wish to shift to accounts roles

• Understand Core Accounting Concepts
• Record and Manage Business Transactions
• Maintain Books of Accounts
• Prepare Final Accounts
• Understand & Apply GST Basics
• Reconcile Bank Records
• Gain Job-Ready Skills for Accounting Roles
• Build a Path to Further Learning

Accounting Principles & Bookkeeping Basics

Introduction to Accounting

• What is Accounting?
• Importance of Accounting in Business
• Types of Accounting (Financial, Management, Cost, etc.)
• Basic Terms: Assets, Liabilities, Equity, Revenue, Expenses

Accounting Principles & Concepts

• GAAP (Generally Accepted Accounting Principles)
• Double Entry System
• Accounting Equation: Assets = Liabilities + Equity
• Types of Accounts (Personal, Real, Nominal)

Journal Entries

• Rules of Debit & Credit
• Format of a Journal
• Recording Basic Transactions
• Practical Exercises

Ledger Posting

• Creating Ledger Accounts
• Posting from Journal to Ledger
• Balancing of Ledger Accounts
• Hands-on Practice

Trial Balance, Cash Book & Bank Reconciliation

Trial Balance

• Purpose and Preparation of Trial Balance
• Locating Errors in Books
• Suspense Account

Subsidiary Books

• Purchase Book, Sales Book
• Purchase Return & Sales Return Book
• Journal Proper

Cash Book

• Types: Single, Double, Triple Column Cash Book
• Contra Entries, Petty Cash Book
• Practical Transactions

Bank Reconciliation Statement (BRS)

• Reasons for Differences Between Cash Book & Bank Statement
• Steps to Prepare BRS
• Sample Practice Sets

Final Accounts & GST Basics

Depreciation & Provisions

• What is Depreciation?
• Methods: Straight Line, Reducing Balance
• Provisions & Reserves

Final Accounts - Part I

• Trading Account
• Profit & Loss Account
• Format and Preparation

Final Accounts - Part II

• Balance Sheet
• Adjustments in Final Accounts
• Preparation from Trial Balance

GST & Career Guidance

• Introduction to GST (Goods & Services Tax)
• GST Concepts, Tax Slabs, Filing Basics
• Basic Invoicing under GST
• Career Opportunities in Accounting
• Final Assessment / Project

The Data Science & Machine Learning (DSML) course is an intensive 3-month program focused on providing a strong foundation in data science concepts, statistical analysis, machine learning techniques, and deep learning fundamentals. The course blends theory and practice to help learners analyze data, build models, and extract insights using Python.

Through hands-on projects and exposure to essential algorithms and mathematical foundations, learners will gain the skills needed to approach real-world data problems with confidence.

This course is ideal for:



• Aspiring data scientists and machine learning enthusiasts.
• Graduates and working professionals from engineering, mathematics, or IT backgrounds.
• Individuals with basic knowledge of Python and math, looking to enter the data science field.
• Developers aiming to expand their skills into analytics and AI.
• Some familiarity with programming and mathematics is recommended but not mandatory.

By the end of this course, learners will:



• Understand and apply core statistical and machine learning concepts.
• Work with Python for data analysis, visualization, and model development.
• Implement algorithms for regression, classification, and unsupervised learning.
• Explore advanced techniques like regularization, kernel methods, and ensemble learning.
• Understand deep learning fundamentals and basic neural networks.
• Gain proficiency in mathematical foundations like linear algebra, optimization, and probability.
• Apply Monte Carlo simulations in data-driven decision making.
• Build end-to-end data science workflows for real-world problem solving.

• Importing, Summarizing & Visualizing Data
• Statistical Learning
• Monte Carlo Methods
• Unsupervised Learning
• Regression
• Regularization and Kernel Methods
• Classification
• Decision Trees and Ensemble Methods
• Deep Learning
• Linear Algebra and Functional Analysis
• Multivariate Differentiation and Optimization
• Probability and Statistics
• Python Primer

The Core Digital Skills Course is a practical 3-month program designed to build essential computer literacy and digital proficiency for everyday life, education, and the workplace. Whether you're a beginner or someone brushing up on foundational skills, this course covers the key areas: computer fundamentals, typing, office tools (Word, Excel, PowerPoint), internet basics, digital communication, and online safety.

This Course is Suitable For:



• Beginners with little or no prior computer experience.
• Students, job seekers, or professionals looking to improve their digital skills.
• Homemakers or senior citizens wanting to gain confidence in using computers.
• Anyone preparing for a digital workplace or online education environment.

By the end of this course, learners will:



• Understand the fundamentals of computers, hardware/software, and operating systems.
• Confidently use typing tools and keyboard shortcuts to boost productivity.
• Create and manage files, documents, spreadsheets, and presentations using MS Office or Google Suite.
• Navigate the internet safely and effectively using search engines and browsers.
• Send and receive emails, manage a Gmail account, and use communication tools like Google Meet.
• Understand cybersecurity essentials, including passwords, phishing, and privacy.
• Make basic use of digital payments and access government services online.
• Complete mini-projects applying what they've learned in real-world contexts.

Digital Fundamentals & Typing

Introduction to Computers



• Input, Output, and Storage Devices
• Hardware vs Software
• Introduction to Operating Systems (Windows)

Operating a Computer



• Booting, Login, Desktop Basics
• Taskbar, Start Menu, File Explorer
• Creating & Organizing Files and Folders
• Using Keyboard & Mouse Effectively

Typing & Shortcuts



• Touch Typing Basics – Practice Tools
• Keyboard Layout and Common Shortcuts
• Using Notepad and WordPad
• Speed & Accuracy Practice

Maintenance & Troubleshooting



• Basic Computer Maintenance
• Antivirus Awareness
• Understanding Common Errors & Quick Fixes
• Practicing Safe Handling

Office Tools Mastery

Word Processing (MS Word / Google Docs)



• Creating, Saving & Formatting Documents
• Bullets, Numbering, Tables, and Images
• Page Layout, Margins, and Printing
• Real-World Document Practice (e.g., resume, letter)

Spreadsheets (MS Excel / Google Sheets)



• Workbook, Worksheet, Rows/Columns
• Basic Formulas: SUM, AVERAGE, COUNT
• Formatting Data, Using Charts
• Real-Life Application: Budget, Attendance Sheet

Presentations (PowerPoint / Google Slides)



• Slides, Themes, and Layouts
• Inserting Images, Charts, Animations
• Presentation Tips
• Creating a Short Presentation

Office Tools Mini Project



• Create a document (e.g., CV or bio)
• Prepare a budget sheet
• Build a simple 3-slide presentation
• Peer review & submission

Internet, Email & Digital Tools

Internet Basics



• What is the Internet?
• Web Browsers & Search Engines
• Effective Searching (keywords, filters)
• Bookmarking & Browsing Safely

Email & Communication Tools



• Creating & Managing a Gmail Account
• Sending, Receiving, and Replying to Emails
• Attachments, Folders, and Labels
• Using Google Meet & Calendar Basics

Digital Literacy & Online Safety



• Cybersecurity Basics: Passwords, Phishing, Scams
• Digital Footprint & Privacy
• UPI & Digital Payment Overview
• Accessing Government Portals (DigiLocker, Umang)

The AI Foundation & Applications Program (AIFAP) is a comprehensive 4-month course designed to equip learners with the foundational and practical skills needed in Artificial Intelligence. Covering everything from basic concepts and Python programming to machine learning, deep learning, and real-world applications like computer vision or NLP, this program is perfect for stepping into the world of AI with confidence.

Students and fresh graduates curious about AI and data science.



• Working professionals looking to upskill or transition into AI/ML roles.
• Beginners with no prior AI experience but some familiarity with basic math and programming concepts.
• Anyone interested in exploring how AI is transforming industries.

By the end of this program, participants will:



• Understand the fundamentals of AI, its types, and its real-world impact.
• Be proficient in Python for AI applications, including libraries like NumPy and Pandas.
• Gain hands-on experience in data handling, preprocessing, and visualization.
• Learn core machine learning algorithms for regression and classification.
• Build and train neural networks using TensorFlow and Keras.
• Choose and apply either Computer Vision or NLP techniques in a project.
• Explore advanced AI topics such as Generative AI and Responsible AI.
• Complete a capstone project that demonstrates their AI skills on a real-world problem.

Introduction to AI & Python for AI

Module 1: Introduction to Artificial Intelligence



• What is AI? History & Evolution
• Applications of AI in daily life
• Types of AI: Narrow, General, and Super AI
• Ethical concerns and future of AI

Module 2: Python for AI



• Python Basics: Variables, Data Types, Operators
• Control Structures (if-else, loops)
• Functions and Modules
• Data Structures: Lists, Tuples, Dictionaries
• File handling
• Introduction to NumPy and Pandas

Data Handling & Machine Learning Basics

Module 3: Data Handling & Visualization



• Data collection and cleaning
• Exploratory Data Analysis (EDA)
• Data preprocessing techniques
• Data visualization using Matplotlib and Seaborn

Module 4: Introduction to Machine Learning



• Supervised vs Unsupervised Learning
• Regression (Linear, Multiple)
• Classification (KNN, Decision Trees, Logistic Regression)
• Introduction to Scikit-Learn

Deep Learning & Real-World Applications

Module 5: Neural Networks & Deep Learning



• What is Deep Learning?
• Basics of Neural Networks (Perceptron, activation functions)
• Introduction to TensorFlow and Keras
• Building and training basic neural networks
• Overfitting and regularization

Module 6: Computer Vision or NLP (Choose One)

Computer Vision



• Image basics and OpenCV
• Convolutional Neural Networks (CNNs)
• Image classification project

Natural Language Processing (NLP)



• Text preprocessing
• Sentiment Analysis
• Text classification using RNN or simple transformers

Advanced Topics & Capstone Project

Module 7: AI in Industry



• Use cases in healthcare, retail, agriculture, etc.
• AI in automation and chatbots
• Introduction to Generative AI (ChatGPT, DALL·E, etc.)
• Responsible AI & Model Explainability

Module 8: Capstone Project



• Choose a real-world problem
• Collect and prepare data
• Build, train, and evaluate a model
• Document and present the solution

The Comprehensive Digital Marketing Course (CDMC) is a hands-on 3-month program that prepares learners to excel in the dynamic world of digital marketing. It covers everything from foundational concepts and strategy development to advanced execution across SEO, SEM, content marketing, social media, and email marketing.

Participants will also learn to analyze data and measure campaign ROI, culminating in a capstone project where they plan and execute a real-world digital marketing campaign.

This course is perfect for:



• Aspiring digital marketers and content creators.
• Business owners and entrepreneurs wanting to promote their brand online.
• Students or graduates looking to build a career in digital marketing.
• Professionals in traditional marketing looking to upskill in digital channels.
• Freelancers aiming to offer digital marketing services.

By the end of this course, learners will:



• Understand the digital marketing ecosystem and how to craft strategies using SMART goals.
• Build and manage websites optimized for conversions and user experience.
• Plan, create, and promote content across various digital formats.
• Master SEO techniques for higher visibility and organic growth.
• Run paid campaigns using Google Ads and optimize them for performance.
• Develop and execute social media marketing strategies across major platforms.
• Build email campaigns using automation, segmentation, and analytics tools.
• Analyze digital campaign performance using key tools and metrics.
• Execute a full-scale digital marketing campaign as part of the capstone project.

Introduction to Digital Marketing and Strategy



• Course Overview and Objectives
• History and Evolution of Digital Marketing
• The Digital Marketing Ecosystem
• Developing a Digital Marketing Strategy
• Setting SMART Goals for Digital Campaigns
• Case Study Analysis

Website Essentials for Digital Marketing



• Website as a Digital Marketing Asset
• Website Design Principles for Conversions
• User Experience (UX) and User Interface (UI) Design
• Mobile Optimization and Responsiveness
• Website Analytics and Tracking
• Building a Basic Website (Hands-on)

Content Strategy and Creation



• Content Marketing Fundamentals
• Content Types and Formats (Blogs, Videos, Infographics, etc.)
• Content Planning and Editorial Calendars
• SEO and Content Optimization
• Content Promotion and Distribution
• Content Creation Workshop

Search Engine Optimization (SEO)



• Introduction to SEO and Its Importance
• Keyword Research and Analysis
• On-Page SEO Techniques
• Off-Page SEO Strategies
• Technical SEO and Site Audits
• SEO Tools and Analytics

Pay-Per-Click Advertising (PPC) and SEM



• Understanding PPC and Google Ads
• Google Ads Campaign Setup
• Keyword Research and Ad Groups
• Ad Copywriting and Ad Extensions
• Bidding Strategies and Budgeting
• Advanced PPC Optimization Techniques

Social Media Marketing (SMM)



• Social Media Strategy Development
• Social Media Content Creation
• Community Building and Engagement
• Social Media Advertising (Facebook, Instagram, Twitter, LinkedIn)
• Social Media Analytics and Reporting
• Social Media Campaign Management

Email Marketing and Analytics



• Email Marketing Essentials
• Building and Segmenting Email Lists
• Email Content Creation and Design
• Email Automation and Drip Campaigns
• Email Deliverability and Compliance
• Digital Marketing Analytics and ROI Measurement

Capstone Project and Course Review



• Capstone Project - Students design and execute a comprehensive digital marketing campaign.
• Project Presentations and Peer Feedback
• Course Review, Q&A, and Next Steps in Digital Marketing

The Front-End Development Bootcamp (FEDP) is an immersive 3-month program designed to turn beginners into job-ready front-end developers. Through a structured, hands-on approach, learners will master HTML, CSS, JavaScript, and modern front-end frameworks like React or Vue. The course emphasizes building responsive, accessible, and secure websites and applications, capped off with a final project and career readiness support.

This bootcamp is ideal for:

• Complete beginners interested in web development.
• Students, job seekers, or career switchers aiming to enter the tech field.
• Designers looking to learn how to bring their designs to life with code.
• Aspiring freelancers or startup founders wanting to build their own websites.

By the end of this program, learners will:

• Understand how the web works and the role of front-end development.
• Build responsive websites using HTML, CSS, and JavaScript.
• Master layout techniques using Flexbox and CSS Grid.
• Create dynamic and interactive web pages with DOM manipulation.
• Gain hands-on experience with modern front-end frameworks like React or Vue.js.
• Use Git and GitHub for version control and collaboration.
• Optimize websites for performance, accessibility, and security.
• Deploy websites online using popular hosting platforms.
• Complete a capstone project integrating real-world tools and best practices.
• Build a personal portfolio and prepare for tech interviews or freelancing work.

Introduction to Web Development



• Understanding the web development ecosystem
• Role of front-end development
• Basics of HTML, CSS, and JavaScript
• Setting up development environments

HTML and CSS Fundamentals



• In-depth HTML structure and elements
• CSS syntax and styling properties
• Building static web pages
• Working with forms and input elements

Responsive Web Design



• Principles of responsive design
• Media queries and breakpoints
• Building mobile-first layouts

JavaScript Basics



• Introduction to JavaScript
• Variables, data types, and operators
• Control flow (if statements, loops)
• Functions and scope

Document Object Model (DOM)



• Understanding the DOM
• DOM manipulation and event handling
• Creating interactive web pages with JavaScript

CSS Layout and Flexbox



• CSS box model and layout properties
• Flexbox for building flexible and responsive layouts

CSS Grid Layout



• CSS Grid for complex grid-based layouts

Advanced JavaScript



• Object-oriented programming in JavaScript
• ES6 features (Arrow functions, classes, promises)
• Asynchronous programming and AJAX

Front-End Frameworks



• Introduction to popular front-end frameworks (e.g., React, Angular, or Vue.js)
• Building user interfaces with a framework
• State management and component-based architecture

Version Control and Git



• Introduction to version control
• Using Git for collaborative development
• Branching, merging, and resolving conflicts]

Web Performance Optimization



• Strategies for optimizing web performance
• Minification and compression techniques
• Image optimization

Web Accessibility



• Understanding web accessibility and its importance
• Creating accessible web content
• Testing and auditing for accessibility compliance

Web Security



• Common web security threats
• Cross-Site Scripting (XSS) and Cross-Site Request Forgery (CSRF) prevention
• Secure coding practices

Deployment and Hosting



• Deploying a website or web application to a web server
• Hosting options and considerations
• Domain registration and DNS configuration

Final Project



• Building a complete front-end project from scratch
• Integrating with back-end services (APIs)
• DCollaborative development using Git
• Presentation of final projects

Job Search and Career Development



• Building a portfolio
• Preparing for job interviews
• Freelancing and remote work opportunities
• Staying updated with industry trends

The Python Fundamentals and Programming Course (PFPC) is an in-depth 4-month program designed for learners who want to master Python from the ground up. Spanning from basic syntax and data types to advanced concepts like multithreading, web scraping, Flask, networking, and IoT programming, this course is ideal for anyone looking to develop robust Python programming skills for software development, automation, data analysis, or system scripting.

The curriculum also includes hands-on modules with libraries like Pandas, Matplotlib, Asyncio, Flask, SQLite, and even touches on Raspberry Pi programming and GUI development.

This course is suitable for:

• Beginners who want to learn Python thoroughly from scratch.
• Students and professionals looking to build careers in software development, data science, or automation.
• Engineers from other domains who want to transition into programming.
• Developers aiming to deepen their Python knowledge for real-world projects.
• Anyone interested in using Python for IoT, web applications, or system-level tasks.

By the end of this program, participants will:

• Understand Python fundamentals including data types, loops, conditionals, and functions.
• Work with files, folders, and input/output operations using built-in Python modules.
• Master object-oriented programming (OOP), metaclasses, decorators, and advanced function usage.
• Use libraries and tools like Pandas, NumPy, Matplotlib, Flask, and SQLite for practical tasks.
• Perform web scraping, HTTP requests, and XML/HTML parsing.
• Explore concurrency with multiprocessing, multithreading, and async programming.
• Build desktop and web applications, APIs, and automation tools.
• Work with networking, sockets, and secure communications using Python.
• Understand deployment, packaging, and virtual environments.
• Apply best practices, debugging, and testing using tools like py.test.
• Develop real-world solutions including IoT, GUI (Tkinter, Kivy), and data visualization projects.

Introduction to Python Fundamentals



• Getting started with Python Language
• Python Data Types, Indentation
• Comments and Documentation, Date and Time, Date Formatting
• Enum, Set, Simple Mathematical Operators
• Bitwise Operators, Boolean Operators
• Operator Precedence, Variable Scope and Binding
• Conditionals, Comparisons, Loops, Arrays
• Multidimensional Arrays, Dictionary, List, List Comprehensions
• List Slicing (selecting parts of lists), groupby(), Linked lists
• Linked lists Node, Filter, Heapq, Tuple, Basic Input and Output
• Files and Folders I/O, os.path, Iterables and Iterators
• Functions, Defining Functions with list arguments
• Functional Programming in Python, Partial Functions, Decorators
• Classes, Metaclasses, String Formatting, String Methods
• Using loops within functions, Importing modules
• Difference between Module and Package, Math Module, Complex math
• Collections module, Operator module, JSON Module, Sqlite3 Module
• The os Module, The locale Module, Itertools Module, Asyncio Module
• Random module, Functools Module, The dis module, The base64 Module
• Queue Module, Deque Module, Web browser Module
• tkinter, pyautogui module, Indexing and Slicing, Plotting with Matplotlib
• graph-tool, Generators, Reduce, Map Functions, Exponentiation, Searching
• Sorting, Minimum and Maximum, Counting, The Print Function
• Regular Expressions (Regex), Copying data, Context Managers (“with” Statement)
• The __name__ special variable, Checking Path Existence and Permissions
• Creating Python packages, Usage of "pip" module: PyPI Package Manager
• pip: PyPI Package Manager, Parsing Command Line arguments
• Subprocess Library, setup.py, Recursion
• Type Hints, Exceptions, Raise Custom Errors / Exceptions
• Commonwealth Exceptions, Urllib, Web scraping with Python
• HTML Parsing, Manipulating XML, Python Requests Post
• Distribution, Property Objects, Overloading, Polymorphism>
• Method Overriding, User-Defined Methods
• String representations of class instances: __str__ and __repr__ methods
• Debugging, Reading and Writing CSV, Writing to CSV from String or List
• Dynamic code execution with `exec` and `eval`
• PyInstaller - Distributing Python Code, Data Visualization with Python
• The Interpreter (Command Line Console), *args and **kwargs, Garbage Collection
• Pickle data serialisation, Binary Data, Idioms, Data Serialization
• Multiprocessing, Multithreading, Processes and Threads, Python concurrency
• Parallel computation, Sockets,Websockets, Python Networking, Python HTTP Server
• Sockets And Message Encryption/Decryption Between Client and Server
• Flask, Introduction to RabbitMQ using AMQPStorm
• Descriptor, tempfile NamedTemporaryFile, Unzipping Files, working with ZIP archives
• Input, Subset and Output External Data Files using Pandas
• Getting start with Gzip, Stack, Working around the Global Interpreter Lock (GIL)
• Deployment, Logging, Web Server Gateway Interface (WSGI)
• Python Server Sent Events, Alternatives to switch statement from other languages
• List destructuring (aka packing and unpacking), Accessing Python source code and bytecode
• Mixins, Attribute Access, ArcPy, Abstract Base Classes (abc), Plugin and Extension Classes
• Immutable datatypes(int, float, str, tuple and frozensets)
• Incompatibilities moving from Python 2 to Python 3
• 2to3 tool, non-offcial Python implementations
• Abstract syntax tree, Unicode and bytes, Python Serial Communication (pyserial)
• Neo4j and Cypher using Py2Neo, Basic Curses with Python, Templates in python, pillow
• The pass statement, CLI subcommands with precise help output
• Database Access, Connecting Python to SQL Server
• PostgreSQL, Python and Excel, Turtle Graphics, Python Persistence
• Design Patterns, hashlib, Creating a Windows service using Python
• Mutable vs Immutable (and Hashable) in Python, configparser, Optical Character Recognition
• Virtual environments, Python Virtual Environment - virtualenv
• Virtual environment with virtual envwrapper, Create virtual environment with virtual envwrapper in windows
• Sys, ChemPy - python package, pygame, Pyglet, Audio, Pyaudio
• Shelve, IoT Programming with Python and Raspberry PI
• kivy - Cross-platform Python Framework for NUI Development
• Pandas Transform: Preform operations on groups and concatenate the results
• Similarities in syntax, Di erences in meaning: Python vs. JavaScript
• Call Python from C#, Ctypes, Writing extensions, Python Lex-Yacc, Unit Testing, py.test, Profiling
• Python speed of program, Performance optimization, Security and Cryptography, Secure Shell Connection in Python
• Python Anti-Patterns, Common Pitfalls, Hidden Features