Harnessing Analytical Artificial Intelligence: Training Course for Data-Driven Decisions

Inspired By: Springer's Artificial Intelligence for Business Analytics Algorithms, Platforms and Applications Scenarios

Course Overview:

This course equips participants with the methods to leverage Analytical Artificial Intelligence for strategic and operational business outcomes. It covers the transformative role of AI in business analytics, including the implementation of AI algorithms and the enhancement of decision-making through Machine Learning.

Participants will explore techniques like Predictive, Descriptive, and Prescriptive Analytics and learn to use AI for data-driven decisions. Real-world case studies will demonstrate AI applications in Customer Sentiment Analysis, Market Segmentation, and Operational Management.

The course also offers insights into Data Preparation Techniques, AI Data Storage Solutions, and the integration of Big Data Analytics with cloud platforms like Amazon AWS, Google Cloud, and Microsoft Azure. With a focus on AI Technology Frameworks and Deployment Strategies, this program aims to transform how businesses use data and AI for success.

 

Target Audience:

  • Business analysts seeking to integrate AI into their analytics processes.
  • Data scientists and Machine Learning professionals aiming to specialize in business applications.
  • Managers and decision-makers need AI-driven insights.
  • Professionals in IT, operations, marketing, and supply chain roles looking to enhance their skill sets in AI and data analytics.

 

Targeted Organizational Departments:

  • Data Analytics and Business Intelligence Teams
  • Marketing and Customer Experience Departments
  • Operations and Supply Chain Management
  • IT and Digital Transformation Divisions

 

Targeted Industries:

  • Retail and E-commerce
  • Finance and Banking
  • Healthcare
  • Manufacturing
  • Logistics and Supply Chain

 

Course Offerings:

By the end of this course, participants will be able to:

  • Apply Analytical Artificial Intelligence to solve business challenges.
  • Utilize AI for Predictive Modeling, Market Segmentation, and Forecasting.
  • Implement Business Intelligence Frameworks and Cloud-based AI solutions.
  • Analyze customer sentiment using advanced data analytics techniques.
  • Deploy AI Technology Frameworks and optimize business processes with AI.

 

Training Methodology:

This course employs an interactive and engaging methodology, combining theoretical learning with practical applications. Participants will explore real-world scenarios through case studies on AI in Business, participate in group discussions on AI Deployment Strategies, and gain hands-on experience with Google Cloud and Amazon AWS. Techniques like simulation exercises, role-playing, and feedback sessions ensure participants are equipped to apply their learning effectively.

 

Course Toolbox:

Participants will receive:

  • Comprehensive course ebooks and reading materials
  • Templates for Predictive Analytics and Data Wrangling
  • Checklists for AI Deployment Strategies

 

Course Agenda:

Day 1: Foundations of Analytical AI

  • Topic 1: Introduction to Analytical Artificial Intelligence and Business Analytics
  • Topic 2: Distinction Between Business Intelligence and Business Analytics
  • Topic 3: Categorization of Analytical Methods: Descriptive, Predictive, and Prescriptive Analytics
  • Topic 4: Overview of AI and Its Role in Data-Driven Decision-Making
  • Topic 5: Business Analytics Technology Framework (BA.TF)
  • Topic 6: Data Sources: Structured, Unstructured, and Semi-Structured Data
  • Reflection & Review: Recap of foundational concepts and group discussion on potential applications.

 

Day 2: Data Preparation and Modeling

  • Topic 1: Data Preparation Techniques: ETL Processes and Data Cleansing
  • Topic 2: Data Storage Solutions: Data Warehouses vs. Data Lakes
  • Topic 3: Introduction to Machine Learning: Supervised, Unsupervised, and Reinforcement Learning
  • Topic 4: Neural Networks: Basics and Applications in Business Analytics
  • Topic 5: Types of Problems in AI: Classification, Regression, and Clustering
  • Topic 6: Business Use Cases for Predictive Analytics
  • Reflection & Review: Interactive session to identify challenges in data preparation and discuss case studies.

 

Day 3: Advanced Analytical Techniques

  • Topic 1: Prescriptive Analytics and Optimization Techniques
  • Topic 2: AI in Customer Sentiment Analysis and Market Segmentation
  • Topic 3: Advanced Data Analysis Methods for Real-Time Insights
  • Topic 4: Automation and AI in Business Processes
  • Topic 5: Case Study: AI Deployment in Retail and Supply Chain Management
  • Topic 6: Continuous Improvement with AI in Operational Management
  • Reflection & Review: Participant presentations on implementing advanced techniques in their domains.

 

Day 4: AI Deployment Strategies

  • Topic 1: Cloud Platforms for AI: Amazon AWS, Google Cloud, and Microsoft Azure
  • Topic 2: Integrating AI Frameworks: TensorFlow, Scikit-Learn, and Others
  • Topic 3: Data Governance and Security in Big Data Environments
  • Topic 4: Deployment Models: Build or Buy Decisions for AI Solutions
  • Topic 5: AI for Recommendation Systems and Retail Analytics
  • Topic 6: Evaluation Metrics for AI Model Effectiveness
  • Reflection & Review: Team exercises on selecting and deploying AI tools for real-world scenarios.

 

Day 5: Practical Applications and Future Trends

  • Topic 1: Application Integration and Testing for AI Models
  • Topic 2: Leveraging AI for Decision Support and Automation
  • Topic 3: Emerging Trends in AI and Business Analytics
  • Topic 4: Case Study: Real-Time Streaming Analytics for Customer Insights
  • Topic 5: Ethical Considerations in AI Implementation
  • Topic 6: Capstone Project: Designing an AI-Driven Business Solution
  • Reflection & Review: Final group discussion and feedback session on course learnings and applications.

 

How This Course is Different from Other AI Courses:

This course distinguishes itself by focusing on real-world applications and decision-making. Unlike generic AI courses, it integrates practical scenarios such as AI in Customer Sentiment Analysis and Supply Chain Optimization. By emphasizing Cloud Platforms, Big Data Analytics, and Business Intelligence Frameworks, the program ensures that participants are equipped with the latest methods and techniques. This course goes beyond theory, offering actionable insights and strategies for leveraging AI to transform business operations.

credits: 5 credit per day

Course Mode: full-time

Provider: Agile Leaders Training Center

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