Implementing AI for Business Professionals (AA-TTML5501)


Course Description

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.

Course Outline

Part 1: What is Data Science?

The story of Data

  • How Big Data exploded and what has changed to make ìdataî the new ìoilî

AI and Machine Learning

  • The history of AI to ML to DL and an introduction to Neural Networks.

Why is this data useful?

  • What it means to be data driven and how our paradigm is changing

Use Cases for Data Science

  • 20+ of the most common business use cases

Understanding the Data Science ecosystem

  • Overview of the key concepts related to Data Science to include open source, distributed computing, and cloud computing

Part 2: Making Data Science work for your organization

How can Data Science help guide your strategy

  • Use Data Science to guide strategy based on insights into your customers, your product performance, your competition, and additional factors

Forming your strategy for Big Data and Data Science

  • Step by step instructions for scoping your data science initiative based on your business goals, stakeholder input, putting together project teams, and determining the most relevant metrics

Implementing AI & Machine Learning (Analytics, Algorithms, and Machine Learning)

  • How to select models and the importance of agile to realize business value

Choosing your tech

  • Choosing your technology for your proposed use case

Building your team

  • The key roles that need to be filled in Big Data and Data Science programs and considerations for outsourcing roles

Governance and legal compliance

  • Principles in privacy, data protection, regulatory compliance and data governance and their impact on legal, reputational, and internal perspectives.
  • Discussions of:
    • PII
    • GDPR

Case Study

  • Explore a high-profile project failure and best practices for Data Science success

What the Future Hold

Course Objectives

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 itís 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 Prerequisites

Students attending this class should have a grounding in Enterprise computing. While thereís 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.

Course Information

Length: 1 day

Format: Lecture and Lab

Delivery Method: n/a

Max. Capacity: 16



Schedule

Contact Us


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1-877-797-2799
info@firefly.cloud

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