AI in Marketing Live Lessons: Master Techniques to Make AI Work for You
Marketers worry that Artificial Intelligence is going to take their jobs, but AI will take your job only if you refuse to use AI.
Artificial intelligence is the flavor of the week–all the cool kids are doing it. And the field of marketing is no exception. Every component of the Marketing Technology stack–the MarTech stack–is being overrun by AI. Marketers dont need to be experts in technology, or statistics, or data science to use AI. They need to be experts in marketing who are willing to work with AI techniques to do their jobs.
AI in Marketing LiveLessons will help you, the marketer, to take advantage of AI techniques on the job. You will learn what AI can do for you, how to recognize when it will work, what the process is to implement it, and who you need to work with to succeed. Dont miss your chance to up-level your skills to take advantage of the most important marketing technology to come along since the Internet.
Learn How To
- Explain the difference between AI and typical software programs
- Identify opportunities for introducing AI into your organization
- Develop a process for implementing AI in Marketing projects
Who Should to Take This Course
- All marketers need to learn how to work with Artificial Intelligence!
- All marketers and customer experience staffers working with MarTech need to understand how AI works and how it can be used effectively to improve result.
- Analytics experts, data science experts, and AI experts who need to understand how to apply their skills to marketing problems.
- Marketing executives and customer experience executives who want an in-depth understanding of AI.
Table of Contents
1 AI in Marketing – Introduction
2 Learning objectives
3 What is Artificial Intelligence
4 What is Big Data
5 What is data science
6 Lesson 1 Exercise – Project Progress
7 Learning objectives
8 How is AI different from traditional software
9 What is Machine Learning
10 What are some examples of marketing AI in action
11 Lesson 2 Exercise – Project Progress
12 Learning objectives
13 How do I know when my problem can be solved with AI
14 How can I introduce AI into my organization
15 How do I develop an AI strategy
16 Lesson 3 Exercise – Project Progress
17 Learning objectives
18 How does feature analysis work
19 What’s agile development
20 How do you design a real AI system
21 Lesson 4 Exercise – Project Progress
22 Learning objectives
23 How does the data process work
24 How does Machine Learning use data
25 How do we measure our progress
26 Lesson 5 Exercise – Project Progress
27 Learning objectives
28 How do we correct errors
29 Which situations raise ethical concerns
30 Can we put humans in the loop
31 Lesson 6 Exercise – Project Progress
32 Learning objectives
33 What’s coming next in AI
34 What’s next for you and AI
35 AI in Marketing – Summary