Learning AI for Business Analysis

Course details

More and more organizations are making investments in digital technologies such as artificial intelligence, machine learning, and robotics. These new technologies have sparked changes to business models, business operations, and customer expectations and experiences. This course was designed to help business analysts and project professionals grasp what these changes mean and how to implement them from a business perspective. Join instructor Angela Wick as she explores natural language generation, speech recognition, swarm intelligence, blockchain, and other exciting new technologies, laying out how each one can fit into your business processes. Plus, she covers how these innovations can impact traditional business analysis practices and explains how the customer journey is affected by digital and AI projects.

Learning objectives
Identify the intelligent automation and digital landscape involved in digital business analysis.
Determine the fundamentals of AI in business analysis and of robotic process automation (RPA).
Explore the essentials of biometrics, blockchain, and machine and deep learning in project transformation.
Break down the elements of the experiment and hypothesis phases, and the customer journey and the user experience.

Concepts

0. Introduction

01 - Transform your business analysis career
02 - AI's impact on business analysis
03 - The mindset of a business analyst with AI
04 - AI landscape and the urgency for change
05 - Transforming into an AI business analyst
06 - Understand the capabilities of AI

1. AI - Language Interactions and Processing

07 - Generative AI for business analysis
08 - Natural language processing
09 - Speech recognition and voice technologies
10 - Chatbots and virtual agents
11 - AI agents and roles for business analysis

2. AI - Processing Non-Language Things

12 - AI outside the bounds of traditional generative AI
13 - Machine and deep learning - Business uses
14 - Biometrics - Business uses
15 - Video and image analysis - Business uses
16 - Swarm intelligence for business process
17 - Blockchain - business uses
18 - Robotic process automation for business analysis
19 - AI and data analytics for business analysis
20 - AI agent to AI agent integration capabilities

3. Impact to Requirements and Business Analysis

21 - Linking AI capabilities together for business analysis
22 - How are requirements similar for business analysis and AI
23 - How are requirements different for business analysis and AI
24 - Linking digital work to business processes
25 - AI projects with agile

4. Technique Highlights

26 - Experiments and hypothesis in AI business analysis work
27 - Business measurements of success
28 - The customer journey and user experience
29 - Monitoring the results of AI capabilities

Conclusion

30 - Next steps with AI in business analysis work

Learning AI for Business Analysis

Authors

Angela Wick