Curriculum
- 10 Sections
- 174 Lessons
- 10 Weeks
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- Predictive Modeling with SPSS9
- Introduction to Business Analytics23
- 2.11- Definition and Scope of Business Analytics
- 2.2Business Analytics (BA)
- 2.3Data Collection and Integration
- 2.4Data Cleaning and Preprocessing
- 2.5Descriptive Analytics
- 2.6Data Exploration and Visualization
- 2.7Predictive Analytics
- 2.8Prescriptive Analytics
- 2.9Optimization and Simulation
- 2.10Text and Sentiment Analysis
- 2.11Data Governance and Security
- 2.12Business Intelligence (BI)
- 2.132- Importance of Data-Driven Decision-Making
- 2.14Informed Decision-Making
- 2.15Competitive Advantage
- 2.16Cost Efficiency
- 2.17Customer Understanding
- 2.18Risk Management
- 2.19Strategic Planning
- 2.20Continuous Improvement
- 2.21Measurable Outcomes
- 2.22Case Studies
- 2.23Rest
- Key Concepts in Business Analytics14
- 3.1Data Collection and Storage
- 3.2Data Cleaning and Preprocessing
- 3.3Descriptive Analytics
- 3.4Predictive Analytics
- 3.5Prescriptive Analytics
- 3.6Business Intelligence (BI)
- 3.7Data Governance and Security
- 3.8Big Data Analytics
- 3.9Key Performance Indicators (KPIs)
- 3.10Data-driven Decision Making
- 3.11Agile Analytics
- 3.12Ethics in Analytics
- 3.13Rest
- 3.14Case Studies
- Tools and Technologies4
- Data Types and Sources17
- 5.11- Data Types
- 5.2Structured Data
- 5.3Unstructured Data
- 5.42- Data Sources
- 5.5Internal Data Sources
- 5.6External Data Sources
- 5.73- Data Collection Methods
- 5.8Surveys and Questionnaires
- 5.9Observation
- 5.10Interviews
- 5.11Sensor Data
- 5.12Web Scraping
- 5.13Transaction Data
- 5.14Social Media Monitoring
- 5.15Secondary Data Analysis
- 5.16Case Studies
- 5.17Rest
- Cleaning and Transformation25
- 6.11- Dealing with Missing Data
- 6.2Identification of Missing Values
- 6.3Removal of Missing Values
- 6.4Imputation of Missing Values
- 6.5Evaluate the Impact
- 6.6Documentation
- 6.7Iterative Process
- 6.82- Outlier Detection and Treatment
- 6.9Identification
- 6.10Removal
- 6.11Transformation
- 6.12Winsorizing
- 6.133- Data Normalization and Standardization
- 6.14Normalization (Min-Max Scaling)
- 6.15Standardization (Z-score Normalization)
- 6.16Robust Scaling (IQR Scaling)
- 6.174- Feature Engineering Techniques
- 6.18Binning/Discretization
- 6.19One-Hot Encoding
- 6.20Polynomial Features
- 6.21Interaction Terms
- 6.22Feature Scaling
- 6.23Dimensionality Reduction
- 6.24Case Studies
- 6.25Rest
- Exploratory Data Analysis (EDA) with SPSS16
- 7.1Introduction
- 7.21- Basic Statistical Analysis
- 7.3Descriptive Statistics
- 7.4Frequency Distribution
- 7.5Central Tendency and Dispersion
- 7.6Correlation Analysis
- 7.7Inferential Statistics
- 7.82- Data Visualization Techniques:
- 7.9Histograms
- 7.10Box Plots
- 7.11Scatter Plots
- 7.12Bar Charts
- 7.13Heatmaps
- 7.14Pie Charts
- 7.15Line Chart
- 7.16When should I use them?
- Statistical analysis with SPSS24
- 8.11- Descriptive Statistics
- 8.21-1 Measures of Central Tendency and Dispersion
- 8.3Mean, Median, and Mode
- 8.4Variability Measures
- 8.51-2 Frequency Distributions
- 8.6Histograms
- 8.7Percentiles and Quartiles
- 8.81-3 Probability Distributions
- 8.9Normal Distribution
- 8.102- Inferential Statistics
- 8.112-1 Hypothesis Testing
- 8.12Formulate Hypotheses
- 8.13Conduct Statistical Tests
- 8.142-2 Confidence Intervals
- 8.153-1 Confidence Intervals
- 8.16Confidence Interval for Mean
- 8.174-1 Regression Analysis
- 8.18Simple Linear Regression
- 8.19Multiple Regression
- 8.205-1 Correlation Analysis
- 8.21Pearson Correlation
- 8.22SPSS Functionality
- 8.23When should I use them?
- 8.24Case Studies
- Prescriptive Analytics with SPSS8
- Business Intelligence and Reporting34
- 10.11- Dashboard and Visualization Design
- 10.21-1 Principles of Effective Data Visualization
- 10.3Clarity and Simplicity
- 10.4Relevance
- 10.5Consistency
- 10.6Interactivity
- 10.7Storytelling
- 10.8Use of Appropriate Visualization Types
- 10.9Color Usage
- 10.10Data Accuracy and Precision
- 10.111-2 Dashboard Development and Best Practices
- 10.12Define Objectives
- 10.13User-Centric Design
- 10.14Performance Optimization
- 10.15Responsive Design
- 10.16Feedback Mechanisms
- 10.17Regular Updates
- 10.18Testing and Validation
- 10.192- Reporting Tools
- 10.202-1 Introduction to Reporting Tools
- 10.21Tableau
- 10.22Power BI (Microsoft Power BI)
- 10.232-2 Creating Dynamic and Interactive Reports
- 10.24Data Connection
- 10.25Report Design
- 10.26Interactivity
- 10.27Data Refresh and Automation
- 10.28Collaboration and Sharing
- 10.29Security and Access Control
- 10.30Documentation and Training
- 10.31Case Studies
- 10.32Rest
- 10.33Exam
- 10.34Contact Form