This workshop uses field-tested business analytics tools and techniques. The training material is constantly updated to match the latest trends and industry best practices. The workshop is divided into four sessions, taking a deep dive into various interactive approaches, including live lessons, classroom discussions, videos, group activities, pre-class readings, case studies, and individual exercises/quizzes. 

08:30        Registration and Morning Coffee

09:00        Introduction to Data and Analytics

• An introduction to 3 Types of Analytics, two types of insights, and the MAD Framework 
• Understanding Data Science Techniques Taxonomy 
• Looking at the Data Analytics Lifecycle 
• Assessing the role of Business Data, Characteristics, and Types 
• Evaluating the three types of IT Systems 
• Data Lifecycle and Data Quality

10:30        Morning Break

11:00        Predictive Data Analytics – Part I

• Understanding the Fundamentals of Predictive Data Analytics 
• Data Preparation for Predictive Data Analytics 
• Data Profiling for Predictive Data Analytics 
• Hypothesis Testing and P-value 
• Formulating Predictive Data Analytics Models

12:30        Networking Lunch

01:30        Predictive Data Analytics – Part II

• Exploring the four main Key Predictive Data Analytics Techniques 
• Hands-on exercise on Multiple Linear Regression (MLR) 
• Fundamentals of Machine Learning (ML) 
• Four key characteristics of ML Models 
• Ensemble ML Model and Supervised & Unsupervised ML Algorithms

03:30        Afternoon Break

04:00        Summary & Wrap-up    

• Remediating Bad Analytics 
• Data Visualization and Data Storytelling 
• Predictive Data Analytics Case Studies – Oil/Gas, Mining, and Retail/CPG

05:00        End of Workshop