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AI in Business: Strategies for a Data-Driven Enterprise

AI in Business Seminar Series: Explore How AI & Machine Learning Apply in Today’s Business Enterprise, Current Tools, Trends & More

Implementing Big Data & Artificial Intelligence (AI) for Business Professionals is an introductory-level course that delves into the core AI and how AI can be practically exploited in the modern business sense.  This one-day class explores the possibilities that exist to transform your business, and significantly improve KPIs across a broad range of business units and applications.

GK# 101074 Vendor# TTAI2101
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Who Should Attend?

  • Traditional enterprise business decision makers: Product Managers, Tech Leads, Managing Partners, IT Managers
  • Analytics Managers who are leading a team of analysts 
  • Business Analysts who want to understand data science techniques
  • Analytics professionals who want to work in machine learning or artificial intelligence
  • Graduates looking to build a career in Data Science and machine learning
  • Experienced professionals who would like to harness machine learning in their fields to get more insight about customers

What You'll Learn

This course introduces AI from a practical applied business perspective. Through engaging lecture and demonstrations presented by our expert facilitator, students will:

  • Learn which data is most useful to collect now and why it’s important to start collecting that data as soon as possible
  • Understand the intersection between big data, data science and AI (Machine Learning / Deep Learning) and how they can help you reach your business goals and gain a competitive advantage.
  • Understand the factors that go into choosing a Data Science system, including whether to go with a cloud-based solution
  • Explore common tools and technologies to aid in making informed decisions
  • Gain the skills required to build your DS/ AI team

Course Outline
  1. Introduction to AI in Business
    • Explore the relevance and potential impact of AI technologies in modern businesses.
    • What is AI and Why Does It Matter
    • The ROI of AI Adoption
    • Case Studies: AI Transformations
    • AI Ethics and Regulation
    • AI's Role in Different Business Units
    • Quick overview of businesses successfully adopting AI
  2. Data: The Bedrock of AI
    • Identify the types of data most pertinent to AI applications in business.
    • Types of Data: Structured vs Unstructured
    • Importance of Data Collection
    • Data Storage Solutions
    • Data Security and Compliance
    • Data Integration Strategies
    • Evaluating databases suited for AI applications
  3. Big Data, Data Science, and AI – The Power Trio
    • Explore how Big Data, Data Science, and AI synergize for business advantage.
    • The Big Data Ecosystem
    • Data Science Methodologies
    • Machine Learning vs Deep Learning
    • Business Cases for Data Science and AI
    • Tools for Analytics and Data Processing
  4. Cloud-Based vs On-Premise Solutions
    • Make informed decisions on cloud-based vs. on-premise AI solutions.
    • Factors for Choosing a Platform
    • Cloud-Based Pros and Cons
    • On-Premise Pros and Cons
    • Cost Implications
    • Security Considerations
  5. Selecting Tools and Technologies
    • Explore various tools and technologies to facilitate AI adoption.
    • Popular AI Frameworks
    • Visualization Tools
    • Data Cleaning and Preprocessing Tools
    • Analytical Platforms
    • APIs and Libraries
    • Quick tour through a suite of cutting-edge AI tools
  6. Building Your Data Science and AI Teams
    • Explore the key skills and roles to consider when forming a data science/AI team.
    • Core Team Roles
    • Required Skill Sets
    • Training vs Hiring
    • Collaboration Tools
    • Team KPIs and Performance Metrics
    • Leveraging tech for remote collaboration
  7. Generative AI: A New Paradigm for Business
    • Understand how Generative AI can redefine content creation, design, and decision-making in business.
    • What is Generative AI?
    • Applications in Marketing and Design
    • Generative AI in Product Development
    • Ethical and Legal Concerns
    • Generative AI in Business Strategy
    • Auto-Generated Content: See how Generative AI can automatically produce marketing copy and design elements
  8. Emerging Trends in Data & AI for Business
    • Stay ahead of the curve by understanding upcoming trends that will shape the future of AI in business.
    • Federated Learning and Edge AI
    • AI for Sustainability and Social Good
    • AI in Cybersecurity
    • Reinforcement Learning in Business
    • Explainable AI (XAI)
    • Explore the impact of new trends on different business sectors
  9. Next Steps and Action Plan
    • Develop a roadmap to start or advance AI implementation in your organization.
    • Setting Short-term and Long-term Goals
    • Budget and Resource Allocation
    • Scaling AI Projects
    • Ongoing Training and Skills Update

Prerequisites

Students attending this class should have a grounding in Enterprise computing. While there’s no particular class to offer as a prerequisite, students attending this course should be familiar with Enterprise IT, have a general (high-level) understanding of systems architecture, as well as some knowledge of the business drivers that might be able to take advantage of applying AI.

Follow-On Courses

This course is a core component of our AI & Machine Learning Skills Path, designed to trainer participants of all skill levels in modern AI, Machine Learning and Analytics skills across the enterprise. We offer courses in next level AI and Machine Learning, Deep Learning, Natural Language Processing, Applied Machine Learning (Chatbots, Intelligent Web) and many more related titles. Please contact us for details and next step recommendations based on your specific roles and. goals.