Module 1: Introduction to SAP

• Overview of ERP & SAP

• SAP architecture & navigation

• Introduction to SAP modules

• Role of SAP FICO in business processes

Module 2: Organizational Structure in SAP FI

• Company, Company Code, Business Area

• Chart of Accounts, Fiscal Year Variant

• Posting Periods

• Document types & number ranges

Module 3: General Ledger (G/L) Accounting

• Master data creation (G/L accounts)

• Posting transactions in G/L

• Parking & holding documents

• Reversal, recurring & accrual entries

• Bank reconciliation

Module 4: Accounts Payable (AP)

• Vendor master data

• Invoice posting & payment process

• Automatic payment program

• Withholding tax configuration

• Vendor reports & analysis

Module 5: Accounts Receivable (AR)

• Customer master data

• Invoice posting, credit memos & incoming payments

• Dunning process (reminders for overdue invoices)

• Customer reports

• Integration with Sales & Distribution (SD)

Module 6: Asset Accounting (AA)

• Asset master data

• Asset acquisition, transfer & retirement

• Depreciation settings & run

• Asset reports

• Integration with other modules

Module 7: Bank Accounting

• House banks & bank accounts

• Cash journal

• Electronic bank statement (EBS) configuration

• Check management

Module 8: Special Purpose Ledger

• Parallel accounting concepts

• Ledger approach & document splitting

• Segment reporting

Module 9: Controlling (CO) Basics

• Overview of management accounting

• Cost element accounting

• Cost center & profit center accounting

• Internal orders

• Product costing basics

• Profitability Analysis (CO-PA)

Module 10: Integration with Other Modules

• Integration with MM (Procurement cycle)

• Integration with SD (Order to Cash)

• Integration with PP (Production)

Module 11: Reporting in SAP FICO

• Financial statements (Balance sheet, P&L)

• Cost reports

• Standard SAP reports

• Introduction to SAP Fiori & SAP Analytics Cloud

Module 12: SAP S/4HANA Finance (New Features)

• Universal Journal (ACDOCA)

• New Asset Accounting

• New GL & Document Splitting

• Real-time integration with CO

• Central Finance concepts

Module 13: End-to-End Business Process

• Procure to Pay (P2P) cycle

• Order to Cash (O2C) cycle

• Record to Report (R2R) cycle

• Asset lifecycle management

Module 14: Real-Time Project & Case Studies

• Implementation methodology (ASAP / Activate)

• Configuration scenarios

• Business requirements mapping

• Testing & validation

• Support and troubleshooting

Module 15: Interview Preparation & Certification

• SAP FICO interview Q&A

• Hands-on exercises

• SAP Certification guidance (C_TS4FI, C_TS4CO)

• Mock tests

📊 Excel Training Course Content

Module 1: Introduction to Excel (Basics)

• Overview of Excel interface

• Workbook, worksheets, cells, rows & columns

• Data entry, editing & formatting

• Autofill, flash fill & custom lists

• Saving, printing & page setup

Module 2: Formatting & Productivity Tools

• Cell formatting (fonts, colors, borders, number formats)

• Conditional formatting (highlighting rules, data bars, icon sets)

• Sorting & filtering data

• Freeze panes, split windows, zoom & view options

• Find & Replace, Go To Special

Module 3: Basic Formulas & Functions

• Understanding formulas & cell references (Relative, Absolute, Mixed)

• Arithmetic operations (+, -, *, /, %)

• Common functions:

  • SUM, AVERAGE, MIN, MAX

  • COUNT, COUNTA, COUNTBLANK

  • TODAY, NOW

• Text functions: LEFT, RIGHT, MID, LEN, TRIM, CONCATENATE, TEXTJOIN

Module 4: Data Handling & Validation

• Data validation (drop-down lists, input messages, error alerts)

• Removing duplicates

• Using Flash Fill effectively

• Protecting worksheets & workbooks

Module 5: Charts & Visualization

• Creating & customizing charts (Column, Bar, Line, Pie, Area, etc.)

• Combo charts

• Sparklines

• Formatting chart elements

• Best practices for data visualization

Module 6: Advanced Formulas & Functions

• Logical functions: IF, AND, OR, IFERROR, IFS

• Lookup functions: VLOOKUP, HLOOKUP, XLOOKUP, INDEX + MATCH

• Date & time functions: EOMONTH, DATEDIF, NETWORKDAYS, WORKDAY

• Statistical functions: RANK, PERCENTILE, AVERAGEIF(S), SUMIF(S), COUNTIF(S)

• Dynamic arrays: SORT, FILTER, UNIQUE, SEQUENCE

Module 7: PivotTables & PivotCharts

• Creating PivotTables from datasets

• Grouping data (dates, numbers, text)

• Summarizing & filtering PivotTables

• Using slicers & timelines

• Creating PivotCharts

Module 8: Advanced Data Tools

• What-If Analysis: Goal Seek, Data Tables, Scenario Manager

• Power Query (Get & Transform Data)

• Consolidating data from multiple sheets

• Flash Fill for automation

• Removing duplicates & cleaning data

Module 9: Advanced Excel Features

• Named ranges & dynamic ranges

• Array formulas & dynamic arrays

• Data validation with formulas

• Conditional formatting with formulas

• Hyperlinks & linking sheets/workbooks

Module 10: Macros & Automation

• Introduction to Macros

• Recording & running macros

• Assigning macros to buttons

• Basics of VBA (optional for advanced learners)

Module 11: Collaboration & Security

• Sharing workbooks

• Tracking changes & comments

• Protecting worksheets/workbooks

• Restricting editing with passwords

Module 12: Real-Time Case Studies & Projects

• Sales & revenue dashboard

• HR employee database management

• Financial budgeting template

• KPI reporting with PivotTables & charts

📘 Tally Prime Training Course Content

Module 1: Introduction to Tally Prime

• Overview of Tally ERP & Tally Prime

• Features & advantages of Tally Prime

• Installing and navigating Tally Prime

• Understanding company creation & setup

• Basics of accounting in Tally

Module 2: Company & Masters Setup

• Creating, altering & deleting company

• Setting financial year, security & user controls

• Groups & ledgers creation

• Inventory masters (Stock groups, Units, Stock items, Godowns)

• Cost centres & categories

Module 3: Basic Accounting in Tally Prime

• Double-entry accounting concepts

• Voucher types (Payment, Receipt, Journal, Contra, Sales, Purchase)

• Posting transactions

• Editing & deleting vouchers

• Day Book & Ledger Reports

Module 4: Inventory Management

• Inventory masters setup

• Stock inwards & outwards entries

• Sales & purchase with inventory

• Delivery note, receipt note, rejection in/out

• Stock summary & movement analysis

Module 5: Banking in Tally Prime

• Cheque printing

• Bank reconciliation

• Deposit slips & payment advices

• E-payments setup & transactions

Module 6: GST (Goods & Services Tax) in Tally Prime

• GST setup & configuration

• Creating GST ledgers & tax rates

• Recording GST sales & purchase transactions

• Input Tax Credit (ITC)

• GST reports & returns filing

Module 7: TDS & TCS in Tally

• Enabling TDS & TCS in Tally

• Creating TDS/TCS ledgers & masters

• Recording TDS/TCS entries

• Generating statutory reports

Module 8: Payroll Management

• Enabling payroll in Tally Prime

• Creating employee masters & pay heads

• Salary structure & processing

• Payroll reports (Payslips, Attendance, PF, ESI)

Module 9: Advanced Features

• Budgets & controls

• Cost centres & cost categories reporting

• Interest calculations

• Multi-currency transactions

• Order processing (Sales/Purchase orders)

• Job costing

Module 10: Tally Prime Reports & MIS

• Balance Sheet, Profit & Loss Account

• Trial Balance, Cash Flow, Fund Flow

• Stock reports & ageing analysis

• Ratio analysis

• Statutory compliance reports

Module 11: Data Management in Tally

• Backup & restore

• Split company data

• Export, import & e-mail reports

• Security control & user management

Module 12: Real-Time Business Scenarios & Project Work

• Complete accounting cycle (Journal → Ledger → Trial Balance → Final Accounts)

• GST return filing process

• Payroll for employees

• Inventory & sales reporting

• MIS Dashboard for decision making

Python Training Course Content

Module 1: Introduction to Python

• What is Python? Features & Applications

• Installing Python & IDEs (PyCharm, VS Code, Jupyter Notebook)

• Writing & executing Python programs

• Python syntax, indentation, and comments

• Variables, data types & type conversion

• Input & Output functions

Module 2: Operators & Expressions

• Arithmetic, Relational & Logical operators

• Assignment & Bitwise operators

• Identity & Membership operators

• Operator precedence

Module 3: Control Flow

• Conditional statements (if, if-else, nested if)

• Loops (for, while)

• Break, continue & pass statements

• Iterating with range(), enumerate(), zip()

Module 4: Data Structures in Python

• Strings – slicing, formatting, string methods

• Lists – creation, indexing, slicing, list methods

• Tuples – immutable sequences, unpacking

• Sets – operations, set methods

• Dictionaries – key-value pairs, dictionary methods

• List & dictionary comprehensions

Module 5: Functions & Modules

• Defining & calling functions

• Arguments (positional, keyword, default, variable-length)

• Return values

• Lambda functions

• Scope & namespaces

• Creating & importing modules

• Built-in modules (math, datetime, os, sys, random, etc.)

Module 6: File Handling

• Opening & closing files

• Reading & writing text/binary files

• File pointers & modes

• Exception handling in file operations

Module 7: Exception Handling

• Errors vs Exceptions

• Try, Except, Finally blocks

• Raising exceptions

• Custom exceptions

Module 8: Object-Oriented Programming (OOPs)

• Classes & Objects

• Constructors & Destructors

• Inheritance (single, multiple, multilevel, hierarchical)

• Polymorphism (overloading, overriding)

• Encapsulation & Abstraction

• Magic/Dunder methods (__init__, __str__, etc.)

Module 9: Advanced Python Concepts

• Iterators & Generators (yield, next())

• Decorators

• Context Managers (with statement)

• Regular Expressions (re module)

• Virtual environments & package management (pip, venv)

Data Science Training Course Content

Module 1: Introduction to Data Science

• What is Data Science? Lifecycle & applications

• Roles: Data Analyst vs Data Scientist vs ML Engineer

• Tools overview: Python, R, SQL, Excel, Power BI, Jupyter Notebook

• Case studies in different industries

Module 2: Python for Data Science

• Python basics: variables, data types, operators

• Control flow (if, loops), functions, OOPs basics

• Libraries:

  • NumPy (arrays, numerical operations)

  • Pandas (DataFrames, data cleaning, manipulation)

  • Matplotlib & Seaborn (visualizations)

Module 3: Statistics & Probability

• Descriptive statistics (mean, median, mode, variance, std dev)

• Probability concepts & distributions (Normal, Binomial, Poisson)

• Inferential statistics (Hypothesis testing, t-test, chi-square test, ANOVA)

• Correlation & covariance

• Sampling techniques & Central Limit Theorem

Module 4: Data Wrangling & Cleaning

• Handling missing values

• Outlier detection & treatment

• Data transformation (scaling, normalization, encoding)

• Feature engineering & feature selection

Module 5: Exploratory Data Analysis (EDA)

• Univariate, bivariate & multivariate analysis

• Visualization techniques (histograms, boxplots, heatmaps, pair plots)

• Insights generation from datasets

Module 6: SQL for Data Science

• Database basics & SQL queries

• SELECT, WHERE, GROUP BY, HAVING, ORDER BY

• Joins & subqueries

• Window functions

• Connecting Python with SQL

Module 7: Machine Learning (ML)

Supervised Learning

• Regression (Linear, Multiple, Polynomial, Logistic Regression)

• Classification (KNN, Decision Trees, Random Forest, Naïve Bayes, SVM, XGBoost)

• Model evaluation metrics (accuracy, precision, recall, F1-score, ROC-AUC)

Unsupervised Learning

• Clustering (K-Means, Hierarchical, DBSCAN)

• Dimensionality Reduction (PCA, t-SNE)

Model Optimization

• Cross-validation

• Hyperparameter tuning (Grid Search, Random Search)

• Bias-variance tradeoff

Module 8: Advanced Topics

• Natural Language Processing (NLP) basics

  • Text preprocessing, Bag of Words, TF-IDF

  • Sentiment analysis

• Time Series Analysis

  • ARIMA, SARIMA, Prophet models

• Deep Learning (Intro)

  • Neural networks, TensorFlow/Keras basics

Module 9: Data Visualization & BI Tools

• Advanced visualizations with Python (Seaborn, Plotly)

• Dashboards with Power BI / Tableau

• Storytelling with data

Module 10: Big Data & Cloud (Intro)

• Hadoop & Spark basics

• Using Google Colab, AWS, Azure for ML models

• MLOps basics (CI/CD for ML)

Module 11: Capstone Projects

Real-world projects such as:

• Predicting house prices (Regression)

• Customer churn prediction (Classification)

• Market basket analysis (Unsupervised Learning)

• Sentiment analysis of tweets (NLP)

• Sales forecasting (Time Series)

• Building an interactive dashboard (Power BI/Tableau)

Module 12: Career Prep

• Data Science interview questions (Python, ML, SQL, Stats)

• Kaggle competitions & portfolio building

• Resume & LinkedIn optimization for Data Science roles

• Guidance for certifications (e.g., Microsoft, Google, IBM Data Science)

📅 3-Month Data Analytics Learning Roadmap

Month 1: Excel & Data Foundations

Week 1: Excel Basics & Productivity

• Excel interface, formatting, shortcuts

• Formulas (SUM, AVERAGE, MIN, MAX, COUNT, IF)

• Sorting, filtering, conditional formatting

• Case Study: Sales Data Cleaning

Week 2: Advanced Excel for Analytics

• VLOOKUP, HLOOKUP, INDEX + MATCH, XLOOKUP

• Text, Date & Time functions

• Data validation (drop-downs)

• Case Study: HR Employee Database

Week 3: PivotTables & Dashboards

• PivotTables, PivotCharts

• Slicers, Timelines

• What-if Analysis, Solver

• Dashboard Design Principles

• Project: Build a Sales Dashboard in Excel

Week 4: Statistics Basics

• Mean, Median, Mode, Variance, Std Dev

• Probability distributions

• Correlation vs. Causation

• Hypothesis testing (t-test basics)

• Assignment: Analyze a survey dataset in Excel

Month 2: SQL & Data Visualization (Power BI/Tableau)

Week 5: SQL Fundamentals

• Databases & SQL basics

• SELECT, WHERE, ORDER BY

• GROUP BY, HAVING

• Case Study: Customer Orders Dataset

Week 6: Intermediate SQL

• Joins (INNER, LEFT, RIGHT, FULL)

• Subqueries & Common Table Expressions (CTEs)

• Window functions (ROW_NUMBER, RANK, PARTITION BY)

• Project: Build insights on E-commerce database

Week 7: Power BI/Tableau Basics

• Importing & transforming data

• Data modeling (relationships, hierarchies)

• Visualizations (charts, maps, KPIs)

• Case Study: Sales & Profit Report

Week 8: Advanced Dashboards

• Drill-through, filters, slicers

• Bookmarks & storytelling

• Publishing dashboards to cloud

• Project: Interactive Business Dashboard

Month 3: Python for Analytics & Capstone Projects

Week 9: Python Basics for Analytics

• Python setup & Jupyter Notebook

• Variables, data types, loops, functions

• Libraries: NumPy (arrays, math ops)

• Case Study: Numerical Analysis with NumPy

Week 10: Pandas & Data Visualization

• Pandas DataFrames: cleaning & wrangling

• Handling missing values, duplicates

• Visualization with Matplotlib & Seaborn

• Assignment: Exploratory Data Analysis on Sales Dataset

Week 11: Applied Analytics Projects

• HR Analytics: Attrition Analysis (Excel + SQL)

• Finance Analytics: Budget vs. Actual Dashboard (Power BI)

• Marketing Analytics: Campaign Performance (Python + Pandas)

Week 12: Capstone + Career Prep

• Capstone Project: End-to-End Analytics Solution (SQL + Python + BI)

• Resume building with project portfolio

• Mock interview Q&A

• Certification preparation (Google/Microsoft/Tableau)

📘 Accounting & Taxation Training Course Content

Module 1: Fundamentals of Accounting

• Basics of accounting & double-entry system

• Accounting principles & standards

• Journal, Ledger & Trial Balance

• Adjustment entries

• Final accounts (P&L, Balance Sheet, Cash Flow)

• Bank reconciliation

Module 2: Computerized Accounting with Tally Prime

• Company creation & setup

• Ledger & group creation

• Voucher entries (Payment, Receipt, Journal, Contra, Sales, Purchase)

• Inventory management

• Cost centers & budgeting

• Reports (Trial Balance, Balance Sheet, P&L)

Module 3: Goods & Services Tax (GST)

• Introduction to GST & indirect taxation

• GST structure (CGST, SGST, IGST, UTGST)

• Input Tax Credit (ITC)

• GST registration process

• GST returns filing (GSTR-1, GSTR-3B, Annual return)

• GST reports in Tally Prime

• E-invoicing & E-way bill

Module 4: Income Tax (Direct Taxation)

• Basics of Income Tax Act

• Residential status & tax liabilities

• Income heads (Salary, House Property, Business, Capital Gains, Other sources)

• Tax calculation (slabs, exemptions, deductions under 80C–80U)

• Advance tax & self-assessment tax

• Filing ITR forms (ITR-1 to ITR-5)

• TDS concepts (Tax Deducted at Source) & filing TDS returns

Module 5: Payroll & Compliance

• Payroll process & salary structuring

• Provident Fund (PF) & Employee State Insurance (ESI)

• Professional tax & labour law basics

• Payroll in Tally Prime

• Generating payslips & compliance reports

Module 6: Advanced Excel for Accounting & Taxation

• Accounting templates in Excel

• MIS reports

• Data validation & conditional formatting

• PivotTables for financial reports

• Automating reports with formulas (VLOOKUP, XLOOKUP, IF, SUMIFS, etc.)

Module 7: Corporate & Business Compliance

• Company incorporation process (overview)

• ROC compliance basics

• Overview of auditing & assurance

• Business taxation & corporate tax filing basics

Module 8: Practical Case Studies & Projects

• End-to-end accounting cycle (Journal → Ledger → Trial Balance → Final Accounts)

• GST return filing (live practice using GST portal)

• Income Tax return filing (using utility/software)

• Payroll processing for a company

• Preparation of MIS dashboard in Excel

Module 9: Career Preparation

• Resume building for Accounts & Taxation roles

• Common interview questions in Accounts, GST, and Taxation

• Practical assignments & mock tests

• Guidance for certifications (Tally, GST Practitioner, Income Tax certifications)