AI in Digital Marketing Training Course
AI (Artificial Intelligence) is intelligence for machines to accomplish specific tasks by recognizing patterns in data. AI enables users to growth hack the success of digital marketing campaigns.
This instructor-led, live training (online or onsite) is aimed at marketers who wish to use AI to improve improve digital marketing strategies through valuable customer insights.
By the end of this training, participants will be able to:
- Leverage AI software to improve the way brands connect to users.
- Use chatbots to optimize the user-experience.
- Increase productivity and revenue through the automation of tasks.
Format of the Course
- Interactive lecture and discussion.
- Lots of exercises and practice.
- Hands-on implementation in a live-lab environment.
Course Customization Options
- To request a customized training for this course, please contact us to arrange.
Course Outline
Introduction
AI in Digital Marketing
- What is AIDM?
- The application of AIDM
Content Curation and Creation
- Streamlining content with AI tools
- Working with Curata, BuzzSumo, Crayon, and Scoop-It
Google Cloud AI
- Creating and scaling chatbots
- Integrating chatbots on a web application
SEO Optimization
- Working with Market Brew
Email Task Automation
- Automating email tasks with Siftrock
Tracking and Reporting
- Tracking and reporting user behavior with BlueShift
- Tracking and reporting data from social media platforms with Zoomph
Summary and Conclusion
Requirements
- An understanding of digital marketing
Audience
- Marketers
Open Training Courses require 5+ participants.
AI in Digital Marketing Training Course - Booking
AI in Digital Marketing Training Course - Enquiry
AI in Digital Marketing - Consultancy Enquiry
Upcoming Courses
Related Courses
LangChain: Building AI-Powered Applications
14 HoursThis instructor-led, live training in the US (online or onsite) is aimed at intermediate-level developers and software engineers who wish to build AI-powered applications using the LangChain framework.
By the end of this training, participants will be able to:
- Understand the fundamentals of LangChain and its components.
- Integrate LangChain with large language models (LLMs) like GPT-4.
- Build modular AI applications using LangChain.
- Troubleshoot common issues in LangChain applications.
LangChain Fundamentals
14 HoursThis instructor-led, live training in the US (online or onsite) is aimed at beginner-level to intermediate-level developers and software engineers who wish to learn the core concepts and architecture of LangChain and gain the practical skills for building AI-powered applications.
By the end of this training, participants will be able to:
- Grasp the fundamental principles of LangChain.
- Set up and configure the LangChain environment.
- Understand the architecture and how LangChain interacts with large language models (LLMs).
- Develop simple applications using LangChain.
AI Automation with n8n and LangChain
14 HoursThis instructor-led, live training in the US (online or onsite) is aimed at developers and IT professionals of all skill levels who wish to automate tasks and processes using AI without writing extensive code.
By the end of this training, participants will be able to:
- Design and implement complex workflows using n8n's visual programming interface.
- Integrate AI capabilities into workflows using LangChain.
- Build custom chatbots and virtual assistants for various use cases.
- Perform advanced data analysis and processing with AI agents.
Small Language Models (SLMs): Applications and Innovations
14 HoursThis instructor-led, live training in the US (online or onsite) is aimed at beginner-level to intermediate-level data scientists and developers who wish to implement and leverage Small Language Models in various applications.
By the end of this training, participants will be able to:
- Understand the architecture and functionality of Small Language Models.
- Implement SLMs for tasks such as text generation and sentiment analysis.
- Optimize and fine-tune SLMs for specific use cases.
- Deploy SLMs in resource-constrained environments.
- Evaluate and interpret the performance of SLMs in real-world scenarios.
Small Language Models (SLMs) for Domain-Specific Applications
28 HoursThis instructor-led, live training in the US (online or onsite) is aimed at intermediate-level data scientists and machine learning engineers who wish to create and apply small language models tailored for specific domains such as legal, medical, and technical fields.
By the end of this training, participants will be able to:
- Understand the importance and application of domain-specific language models.
- Curate and preprocess specialized datasets for model training.
- Train and fine-tune language models for domain-specific applications.
- Evaluate and benchmark models using domain-relevant metrics.
- Deploy domain-specific language models in real-world scenarios.
Small Language Models (SLMs) for Human-AI Interactions
14 HoursThis instructor-led, live training in the US (online or onsite) is aimed at intermediate-level data scientists, machine learning and AI researchers who wish to create engaging and efficient AI-powered conversational experiences with small language models.
By the end of this training, participants will be able to:
- Understand the fundamentals of conversational AI and the role of SLMs.
- Design and implement user-centric AI interactions.
- Develop and train SLMs for interactive applications.
- Evaluate and improve the effectiveness of human-AI communication using appropriate metrics.
- Deploy scalable and ethical AI-driven conversational interfaces in real-world scenarios.
Small Language Models (SLMs): Developing Energy-Efficient AI
21 HoursThis instructor-led, live training in the US (online or onsite) is aimed at advanced-level machine learning engineers and AI researchers who wish to develop energy-efficient AI solutions with small language models that are both powerful and environmentally friendly.
By the end of this training, participants will be able to:
- Understand the impact of AI on energy consumption and the environment.
- Apply model compression and optimization techniques to reduce the size and energy usage of AI models.
- Utilize energy-efficient hardware and software frameworks for AI deployment.
- Implement best practices for sustainable AI development.
- Advocate for and contribute to sustainable practices in the AI industry.
Small Language Models (SLMs) for On-Device AI
21 HoursThis instructor-led, live training in the US (online or onsite) is aimed at intermediate-level IT professionals who wish to deploy small language models directly onto devices with limited processing capabilities, opening up possibilities for innovative applications in various sectors.
By the end of this training, participants will be able to:
- Understand the challenges and solutions for implementing AI on compact hardware.
- Optimize and compress AI models for efficient on-device deployment.
- Utilize modern AI frameworks and tools for on-device model implementation.
- Design and develop real-time AI applications for mobile and IoT devices.
- Evaluate and ensure the security and privacy of on-device AI systems.
SLMs for Educational Tech: Tailoring AI for Learning and Development
14 HoursThis instructor-led, live training in the US (online or onsite) is aimed at intermediate-level educational technologists, instructional designers, and AI developers in education who wish to integrate Small Language Models (SLMs) into educational platforms to enhance teaching and learning processes.
By the end of this training, participants will be able to:
- Understand the role of SLMs in educational technology.
- Design AI-driven learning experiences using SLMs.
- Implement SLMs in various educational settings.
- Evaluate the effectiveness of SLMs in learning outcomes.
SLMs for Smart Cities: Urban Planning and Management with AI
14 HoursThis instructor-led, live training in the US (online or onsite) is aimed at intermediate-level urban planners, city administrators, and smart city solution developers who wish to implement Small Language Models (SLMs) in smart city projects to improve urban living.
By the end of this training, participants will be able to:
- Understand the application of SLMs in smart cities.
- Integrate SLMs with urban data sets for enhanced decision-making.
- Develop strategies for deploying SLMs in urban management systems.
- Assess the impact of SLMs on urban planning and smart city solutions.
Introduction to Large Language Models (LLMs)
14 HoursThis instructor-led, live training in the US (online or onsite) is aimed at beginner-level to intermediate-level developers who wish to use Large Language Models for various natural language tasks.
By the end of this training, participants will be able to:
- Set up a development environment that includes a popular LLM.
- Create a basic LLM and fine-tune it on a custom dataset.
- Use LLMs for different natural language tasks such as text summarization, question answering, text generation, and more.
- Debug and evaluate LLMs using tools such as TensorBoard, PyTorch Lightning, and Hugging Face Datasets.
Generative AI with Large Language Models (LLMs)
21 HoursThis instructor-led, live training in the US (online or onsite) is aimed at intermediate-level developers who wish to learn how to use generative AI with LLMs for various tasks and domains.
By the end of this training, participants will be able to:
- Explain what generative AI is and how it works.
- Describe the transformer architecture that powers LLMs.
- Use empirical scaling laws to optimize LLMs for different tasks and constraints.
- Apply state-of-the-art tools and methods to train, fine-tune, and deploy LLMs.
- Discuss the opportunities and risks of generative AI for society and business.
Advanced LLMs for NLP Tasks
21 HoursThis instructor-led, live training in the US (online or onsite) is aimed at intermediate-level data scientists, AI developers, and AI enthusiasts who wish to use LLMs to perform various NLP tasks and create novel and diverse content for different purposes.
By the end of this training, participants will be able to:
- Establish a development environment with LLMs and essential tools.
- Expertly perform NLU and NLI tasks with LLMs.
- Extract, infer, and utilize knowledge graphs effectively.
- Generate and manage dialogues using LLMs for conversational applications.
- Evaluate content quality and diversity generated by LLMs and generative AI.
- Apply ethical principles, ensuring fairness and responsible use of LLMs.
Introduction to Google Gemini AI
14 HoursThis instructor-led, live training in the US (online or onsite) is aimed at beginner-level to intermediate-level developers who wish to integrate AI functionalities into their applications using Google Gemini AI.
By the end of this training, participants will be able to:
- Understand the fundamentals of large language models.
- Set up and use Google Gemini AI for various AI tasks.
- Implement text-to-text and image-to-text transformations.
- Build basic AI-driven applications.
- Explore advanced features and customization options in Google Gemini AI.
Google Gemini AI for Transformative Customer Service
14 HoursThis instructor-led, live training in the US (online or onsite) is aimed at intermediate-level customer service professionals who wish to implement Google Gemini AI in their customer service operations.
By the end of this training, participants will be able to:
- Understand the impact of AI on customer service.
- Set up Google Gemini AI to automate and personalize customer interactions.
- Utilize text-to-text and image-to-text transformations to improve service efficiency.
- Develop AI-driven strategies for real-time customer feedback analysis.
- Explore advanced features to create a seamless customer service experience.