Professional Courses

Topics:

• Meaning and Importance of Data Analytics
• Data Analytics Lifecycle
• Types of Data (Structured, Unstructured)
• Data Sources and Data Collection Methods
• Overview of Tools: Excel, SPSS, AMOS, Power BI
• Data Cleaning and Preprocessing Techniques

Practical:

• Working with raw datasets
• Data cleaning and formatting exercises

Topics:

• Excel Interface and Data Handling
• Data Cleaning Techniques in Excel
• Basic Functions: SUM, AVERAGE, COUNT, IF, Statistical functions, Financial functions, Accounting functions, Solver Add-in Functions
• Sorting, Filtering, and Data Validation
• Pivot Tables and Pivot Charts
• Introduction to Data Analysis ToolPak

Practical:

• Dataset analysis using functions
• Creating summary reports using Pivot Tables

Topics:

• Advanced Functions: VLOOKUP, HLOOKUP, INDEX, MATCH
• Logical and Text Functions
• Conditional Formatting
• Dashboard Design Principles
• Introduction to Macros and Automation

Practical:

• Building an interactive Excel dashboard
• Automating repetitive tasks

Topics:

• Introduction to SPSS Interface and Data Entry
• Variable Types and Data Coding
• Descriptive Statistics (Mean, Median, Mode, SD)
• Data Visualization in SPSS
• Correlation Analysis & Regression Analysis
• Parametric and Non-Parametric Test
• Factor Analysis, Cluster Analysis, Discriminant Analysis
• Multidimensional Scaling (Mapping Tools)
• Hierarchical Clustering, Means Clustering

Practical:

• Running descriptive and inferential statistics
• Interpreting SPSS outputs

Topics:

• Hypothesis Testing
• t-tests (Independent & Paired)
• ANOVA (One-way & Two-way)
• Chi-square Test
• Reliability Analysis (Cronbach’s Alpha)
• Report Writing and Interpretation

Practical:

• Hypothesis testing using datasets
• Case study-based statistical analysis

Topics:

• Introduction to SEM and its Applications
• Path Analysis Concepts
• Confirmatory Factor Analysis (CFA)
• Model Specification and Identification
• Model Fit Indices (GFI, AGFI, IFI, TLI, CFI, RMSEA, GFI, etc.)
• Mediation and Moderation Analysis

Practical:

• Building SEM models using AMOS
• Interpreting model outputs

Topics:

• Introduction to Time Series
• Components of Time Series
• Data Visualization & Patterns, Time Series
• Decomposition, Smoothing Techniques, Stationarity Concept, AR, MA, ARMA Models, ARIMA Model, Model Evaluation & Forecasting

Topics:

• Introduction to Power BI and BI Concepts
• Data Import from Multiple Sources
• Data Transformation using Power Query
• Data Modeling and Relationships
• Creating Visualizations (Charts, Tables, Maps)
• Dashboard Design and Storytelling

Practical:

• Building interactive dashboards
• Data visualization exercises

Topics:

• Introduction to DAX (Data Analysis Expressions)
• Advanced Visualizations and Custom Reports
• Filters, Slicers, and Drill-down Features
• Publishing and Sharing Reports
• Integrating Insights for Decision-Making

Practical (Capstone Project):

• End-to-end data analysis project
• Combining Excel, SPSS, AMOS, and Power BI
• Final presentation of insights and dashboards