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Introduction to Artificial Intelligence Applied to Marketing

Corporate
Digital Skills

Business Management and Finance

Duration

50h

PRESENTATION

Training in Introduction to Artificial Intelligence Applied to Marketing provides a comprehensive overview of AI and how it is applied in effective marketing strategies. Throughout this program, participants will explore Key concepts in AI, its historical evolution and the categories of techniques used in this discipline. The training focuses on the application of AI processes in marketing strategies, including market research, product design, advertising strategies, and digital marketing.

The following topics are covered ethical and legal issues related to AI in marketing, including the intellectual property and the ethical implications of AI for consciousness and emotions.

Objectives

  • Understanding the basic concepts Artificial Intelligence (AI) and its application in marketing.

  • Explore the historical development AI and the major schools of thought.

  • Identify the different AI techniques and categories, including Machine Learning and Deep Learning.

  • Addressing the ethical and legal issues related to AI in marketing.

Syllabus

MODULE 1: INTRODUCTION TO ARTIFICIAL INTELLIGENCE

TEACHING UNIT 1. AN INTRODUCTION TO THE BASIC CONCEPTS OF ARTIFICIAL INTELLIGENCE.

  1. Characterization of Artificial Intelligence
  2. Applications of the Nomenclature and Concepts Related to Artificial Intelligence.
  3. Resources Needed to Use AI.
  4. Current Generation of AI Applications.

TEACHING UNIT 2. THE EVOLUTION OF ARTIFICIAL INTELLIGENCE

  1. Timeline and Key Milestones
  2. Schools of thought on which conventional AI is based. Computational

TEACHING UNIT 3. IDENTIFYING THE DIFFERENT TECHNIQUES FOR DEVELOPING ARTIFICIAL INTELLIGENCE.

  1. Categories of Artificial Intelligence
  2. Machine Learning Techniques
  3. Differences Between Machine Learning and Deep Learning
  4. Assistive Technologies. User Interfaces. Computer Vision

TEACHING UNIT 4. AREAS OF APPLICATION OF ARTIFICIAL INTELLIGENCE.

  1. Current AI-Based Applications. Practical Applications.
  2. Problem Solving Using AI Applications.
  3. Context for the Use of AI Tools.
  4. Requirements and Limitations of AI-Based Applications.

TEACHING UNIT 5. ETHICAL AND LEGAL CONTEXT OF ARTIFICIAL INTELLIGENCE

  1. Artificial Intelligence, Consciousness, and Emotions
  2. Critical Schools of Thought
  3. Intellectual Property Rights of Artificial Intelligence.

MODULE 2: ARTIFICIAL INTELLIGENCE PROCESSES APPLIED TO MARKETING STRATEGIES

TEACHING UNIT 1. APPLICATION OF ARTIFICIAL INTELLIGENCE PROCESSES TO THE FIELD OF MARKET RESEARCH

  1. Characterization of AI-Based Applications for Market Analysis
  2. Ethical and Legal Implications for the Industry Regarding the Scope of AI
  3. Use of AI-Based Market Research Techniques and Tools

TEACHING UNIT 2. THE DEVELOPMENT OF AI IN THE FIELD OF PRODUCT OR SERVICE DESIGN

  1. Application of AI Techniques and Tools for Decision Making
  2. Integration of AI Design and Development Methodologies

TEACHING UNIT 3. IMPLEMENTATION OF ARTIFICIAL INTELLIGENCE IN THE FIELD OF ADVERTISING STRATEGY

  1. Characterization of AI-Based Advertising Applications
  2. The Concept of Programmatic Advertising
  3. Using Tools and Techniques to Optimize Advertising Strategy
  4. Brand Image Management
  5. Applying Techniques and Strategies from Success Stories

TEACHING UNIT 4. APPLICATION OF THE LATEST ADVANCES IN ARTIFICIAL INTELLIGENCE TO DIGITAL MARKETING

  1. Most Commonly Used Application Ecosystems and Techniques
  2. Using the Main Social Media Marketing Tools
  3. Creating and Managing a Web Analytics Account
  4. Design and Management of a Web Advertising Campaign
  5. Design and Management of a Social Media Advertising Campaign

MODULE 3: DEVELOPMENT OF CUSTOM ARTIFICIAL INTELLIGENCE SOLUTIONS FOR THE MARKETING FIELD

TEACHING UNIT 1. CREATING A PREDICTIVE MODEL USING A “NO-CODE” TOOL”

  1. BigML Features and Sections
  2. Monitoring the Process for Developing a Predictive Model
  3. Integrating the model created in BigML into a marketing application

TEACHING UNIT 2. APPLICATION OF GCP (GOOGLE CLOUD PLATFORM) TOOLS FOR AI.

  1. Data Management with BigQuery
  2. Creating a Predictive Model with BigQuery
  3. Creating a Dashboard (KPI) with DataStudio
  4. Creating an Intelligent Agent with DialogFlow

LESSON UNIT 3. INTRODUCTION TO AI DEVELOPMENT WITH PYTHON

  1. Proposal for a Machine Learning Algorithm
  2. Executing the code to obtain an AI model
  3. Characterization of an autoencoder and a convolutional neural network
  4. Design and Development Process for an AI Solution
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