Advanced Data Analytics Certification | Analytics Training in Riga

Advanced Data Analytics Certification​ Course Outline

Day 1: Advanced Statistical Analysis and Data Engineering

Module 1: Advanced Data Analytics Foundations

• Evolution of Data Analytics and Key Trends
• Data Science vs. Data Analytics vs. Business Intelligence
• Frameworks for Decision-Making with Data
• Understanding Data Pipelines for Analytics

Module 2: Advanced Statistical Analysis and Hypothesis Testing

• Probability Distributions (Normal, Binomial, Poisson)
• Central Limit Theorem and Bayesian Inference
• Hypothesis Testing (T-Test, ANOVA, Chi-Square)
• Bootstrapping and Confidence Intervals

Module 3: Multivariate Analysis and Dimensionality Reduction

• Principal Component Analysis (PCA)
• Factor Analysis for Feature Selection
• LDA for Classification Problems
• Manifold Learning Techniques (t-SNE, UMAP)

Module 4: Advanced SQL for Data Analytics

• SQL for Analytical Queries (Window Functions, CTEs)
• Query Optimization and Performance Tuning
• Time Series Data Manipulation in SQL
• Recursive Queries and Advanced Joins

Day 2: Data Processing and Predictive Analytics

Module 5: Data Cleaning, Transformation and Feature Engineering

• Handling Missing Data (Imputation and Outlier Detection)
• Encoding Categorical Data (One-Hot, Target Encoding)
• Feature Scaling and Normalization Techniques
• Creating Synthetic Features for Better Models

Module 6: Exploratory Data Analysis (EDA) with Python

• Data Profiling and Summary Statistics
• Identifying Patterns and Outliers with Visualization
• Correlation Analysis and Feature Relationships
• Advanced Data Transformation Methods

Module 7: Predictive Analytics and Machine Learning Models

• Regression Models: Linear, Ridge, Lasso
• Classification Models: Logistic Regression, Decision Trees
• Bias-Variance Tradeoff and Model Validation Strategies
• Model Selection and Performance Metrics

Module 8: Ensemble Learning and Model Optimisation

• Bagging (Random Forest) and Boosting (XGBoost, LightGBM, CatBoost)
• Stacking and Blending Techniques
• Hyperparameter Tuning (Grid Search, Bayesian Optimization)
• Cross-Validation and Model Robustness Testing

Day 3: Unsupervised Learning and Time Series Forecasting

Module 9: Unsupervised Learning and Clustering Techniques

• K-Means, DBSCAN, and Hierarchical Clustering
• Anomaly Detection with Isolation Forests
• Association Rule Mining (Apriori, FP-Growth)
• Customer Segmentation for Business Insights

Module 10: Time Series Analysis and Forecasting

• Understanding Trends and Seasonality
• ARIMA, SARIMA, and Exponential Smoothing
• Machine Learning for Time Series (XGBoost and LSTMs)
• Anomaly Detection in Time Series Data

Module 11: Advanced Data Visualization Techniques

• Customizing Visualizations with Matplotlib and Seaborn
• Interactive Dashboards with Plotly
• Advanced Charting Techniques (Heatmaps, Sankey Diagrams)
• Best Practices for Data Storytelling

Module 12: Explainable AI and Model Interpretability

• Feature Importance and SHAP Values
• Partial Dependence Plots and LIME
• Fairness and Bias Mitigation in Machine Learning
• Ethical Considerations in AI Decision Making

Day 4: Business Intelligence and Real-World Applications

Module 13: Business Intelligence with Tableau

• Data Preparation and Importing Large Datasets
• Creating Advanced Charts and Visualizations
• Interactive Dashboards and Storytelling in Tableau
• Data Blending and Advanced Calculations

Module 14: Data-Driven Decision Making and Optimization Techniques

• A/B Testing and Experimentation
• Decision Trees for Strategic Decision-Making
• Optimizing Business Processes with Data
• Real-World Applications of Data Analytics

Module 15: Data Governance and Quality Management

• Principles of Data Quality and Data Lineage
• Data Cleaning Frameworks for Large-Scale Analytics
• Handling Data Privacy and Compliance Regulations (GDPR, HIPAA)
• Automating Data Validation and Monitoring

Who should attend this Advanced Data Analytics Certification Course?

The Advanced Data Analytics Certification Training is designed for individuals aiming to delve deep into Data Analysis techniques, methodologies, and applications. This course can be beneficial for a wide range of professionals, including:

• Data Scientists
• Data Analysts
• Business Analysts
• Machine Learning Engineers
• Business Intelligence Professionals
• Database Administrators
• Quantitative Researchers

Prerequisites of the Advanced Data Analytics Certification Course

There are no formal prerequisites for attending this Advanced Data Analytics Certification Course.

Advanced Data Analytics Certification Course Overview

Advanced Data Analytics stands at the forefront of enabling businesses and organisations to make data-driven decisions. By leveraging complex datasets, analytics techniques, and tools, professionals can uncover valuable insights, predict trends, and optimise operations, making it a critical skill in today’s data-centric world.

Proficiency in Advanced Data Analytics is crucial for data scientists, business analysts, and IT professionals who aim to excel in predictive analytics, extensive data analysis, and visualisation. Mastering this domain enables them to drive strategic decisions, enhance business outcomes, and maintain a competitive edge in the rapidly evolving digital landscape.

This 4-day training is designed to equip delegates with the knowledge and skills to apply advanced analytics techniques effectively. Participants will learn to navigate complex data, utilise modern analytics tools, and implement best practices in data analysis, preparing them for immediate application in real-world scenarios and advancing their careers.

Course Objectives

• To understand the foundational and advanced principles of data analytics
• To learn to apply statistical models and machine learning algorithms for predictive analytics
• To gain proficiency in using leading analytics software and tools
• To develop skills in data visualisation and interpretation of results for strategic decision-making
• To enhance data handling capabilities, including big data platforms

After completing this Data Analytics Course, delegates will receive a certification, signifying their ability to handle complex analytics projects. This certification boosts career prospects, showcases expertise, and empowers data-driven contributions in organisations.

What’s included in this Advanced Data Analytics Certification Course?

• World-Class Training Sessions from Experienced Instructors
• Advanced Data Analytics Certificate
• Digital Delegate Pack