Master Data Science for BI: 5-Day Intensive IT Training

Course Description

This intensive 5-day course equips IT professionals with essential data science skills for business intelligence. Participants will learn to leverage advanced analytics, machine learning, and AI techniques to extract actionable insights from complex datasets. The course covers the entire data science lifecycle, from data preparation to model deployment, with a focus on practical applications in business intelligence.

Learning Objectives

• Master core data science concepts and their applications in business intelligence
• Develop proficiency in data preprocessing, exploratory analysis, and feature engineering
• Build and evaluate machine learning models for predictive analytics
• Apply advanced techniques in natural language processing and deep learning
• Implement data visualization and storytelling strategies for effective communication
• Understand ethical considerations and best practices in data science for BI

Course Modules

Day 1: Foundations of Data Science for BI

• Introduction to data science and its role in business intelligence
• Data collection, cleaning, and preprocessing techniques
• Exploratory data analysis and statistical inference
• Feature engineering and selection

Day 2: Machine Learning for Predictive Analytics

• Supervised learning algorithms (regression, classification)
• Unsupervised learning techniques (clustering, dimensionality reduction)
• Model evaluation and performance metrics
• Ensemble methods and advanced model tuning

Day 3: Advanced Analytics and AI Techniques

• Time series analysis and forecasting
• Natural language processing for text analytics
• Introduction to deep learning and neural networks
• Anomaly detection and recommendation systems

Day 4: Big Data Technologies and Cloud Platforms

• Distributed computing frameworks (Hadoop, Spark)
• Cloud-based data science platforms (AWS, Azure, GCP)
• Data warehousing and ETL processes
• Real-time analytics and stream processing

Day 5: Data Visualization and Business Applications

• Data visualization techniques and best practices
• Dashboard design for effective BI reporting
• Storytelling with data for executive presentations
• Ethical considerations and data governance
• Case studies and real-world applications

Practical Wins for Participants

• Develop a predictive model to forecast key business metrics
• Create an interactive dashboard for real-time business intelligence
• Implement a text analytics solution for customer feedback analysis
• Design and present a data-driven strategy recommendation to stakeholders