Evolution of Data Analytics: From Descriptive to Predictive & Prescriptive Analytics

Key Industry Trends: AI Integration, Real-Time Analytics, Cloud-Based Analytics

Distinguishing Data Science, Data Analytics, and Business Intelligence

Strategic Decision-Making Frameworks Using Data

Overview of End-to-End Data Pipelines and Their Role in Analytics Workflows

Deep Dive into Probability Distributions: Normal, Binomial, Poisson

Central Limit Theorem & Bayesian Thinking for Inference

Robust Hypothesis Testing: T-Tests, ANOVA, Chi-Square Analysis

Confidence Intervals & Bootstrapping Techniques for Estimation

Principal Component Analysis (PCA) for Reducing Data Complexity

Factor Analysis: Enhancing Feature Selection

Linear Discriminant Analysis (LDA) for Supervised Classification

Non-Linear Reduction Using t-SNE and UMAP for Pattern Recognition

Advanced SQL Queries: Window Functions, CTEs, Subqueries

Performance Tuning & Query Optimization Techniques

Handling Time-Series and Temporal Data in SQL

Advanced Join Techniques & Recursive Querying

Strategies for Handling Missing Data and Outliers

Categorical Variable Encoding: One-Hot, Label, and Target Encoding

Feature Scaling: Normalization, Standardization, Robust Scaling

Advanced Feature Engineering: Polynomial, Interaction, and Synthetic Features

Data Profiling & Summary Analysis

Visual Data Exploration to Detect Patterns & Anomalies

Correlation Mapping and Relationship Insights

Advanced Transformation Techniques for Data Preparation

Building Regression Models: Linear, Ridge, Lasso

Classification Models: Logistic Regression, Decision Trees

Understanding Bias-Variance Tradeoff

Model Validation & Evaluation Metrics: AUC, F1-Score, Confusion Matrix

Bagging (Random Forest) & Boosting (XGBoost, LightGBM, CatBoost)

Stacking and Blending for Improved Model Accuracy

Hyperparameter Optimization: Grid Search, Random Search, Bayesian Optimization

Cross-Validation Techniques and Robustness Testing

K-Means, DBSCAN, and Hierarchical Clustering Algorithms

Anomaly Detection Using Isolation Forests

Market Basket Analysis: Apriori & FP-Growth Algorithms

Customer Segmentation for Personalization & Business Strategy

Decomposing Time Series: Trends, Seasonality, Noise

Traditional Models: ARIMA, SARIMA, Exponential Smoothing

Machine Learning-Based Forecasting: LSTM, Prophet, XGBoost

Real-Time Anomaly Detection in Time Series

Data Presentation Using Matplotlib and Seaborn

Interactive Visualizations with Plotly & Dash

Advanced Charts: Heatmaps, Tree Maps, Sankey Diagrams

Data Storytelling Techniques for Effective Communication

Feature Importance Metrics: SHAP, Permutation Importance

LIME & Partial Dependence Plots for Model Interpretability

Addressing Fairness, Transparency & Bias in AI Models

Ethics in AI: Regulation Awareness & Accountability

Data Ingestion & Preparation in Tableau

Creating Compelling Dashboards and Visual Reports

Advanced Calculations, Filters & Interactive Elements

Data Blending & Storytelling Techniques in BI

A/B Testing for Product and UX Optimization

Decision Trees and Prescriptive Analytics for Strategic Planning

Leveraging Analytics for Operational Efficiency & Cost Optimization

Industry Case Studies and Success Stories

Core Principles of Data Governance & Quality Assurance

Implementing Scalable Data Cleaning Frameworks

Ensuring Compliance: GDPR, HIPAA, and Data Ethics

Automating Validation, Lineage Tracking & Monitoring Pipelines