Utilizing AI to Foster Innovation in the Financial Services Sector

LLM Course dedicated to professionals and experts in the financial services industry.

Course Overview

This course is tailored for financial services professionals aiming to harness the transformative potential of Artificial Intelligence (AI) for innovation. Participants will explore:

  • Fundamentals of Artificial Intelligence
  • Current trends in AI-driven innovations within the financial services sector
  • Analysis and assessment of artificial intelligence solutions
  • Regulations and compliance in AI adoption
  • Cost implications of adopting AI-based solutions
  • Real-world examples highlighting AI-powered innovations
  • Emerging technologies at the intersection of AI and financial services

Learning Outcomes

  • Acquire a solid understanding of the fundamentals of Artificial Intelligence
  • Gain insights on current industry trends in AI-driven Innovations specifically tailored to financial services industry
  • Acquire essential skills for evaluating AI-related proposals relevant to the financial services sector
  • Understanding of regulations and compliance in AI adoption
  • Insights into the actual cost implications of adopting AI-based solutions
  • Examination of real-world examples highlighting AI-powered innovations
  • Exploration of emerging technologies at the intersection of AI and financial services
  • Comprehensive understanding of the journey from concept to production
2 Sessions
Per Week

This course includes:

  • Overview about AI: an exploration of diverse terminologies relatedto AI and machine learning, offering guidance on how to discern whether anapplication is powered by AI or not.
  • Types of AI: explore various AI categories, includingcomputer vision, natural language processing (NLP), machine learning (ML), deeplearning, and more.
  • Current Trends in AI Use Cases within Financial Services : highlighting numerous examples illustrating the application of AI in financial services , emphasizing anotable success story in the field.
  • Key considerations when analysing and assessing AI technologies: the pivotal elements to consider when evaluating and analysing AI technologies.
  • Prerequisites and Common Challenges in AI Projects: the essential prerequisites and common challenges encountered in AI powered projects
  • Effective Data Collection Planning: essentials of gathering and cleaning data to power AI based applications
  • Introduction to Generative AI: Explore the fundamentals of generative AI, including key concepts, history, and the types of generative models.
  • Evolution of Neural Networks to LLMs: Trace the development of neural networks and learn how they have evolved into today's advanced language models. Introduce basic neural network architectures and their limitations, leading to the rise of LLMs.
  • Understanding Transformer Architecture: Delve into the architecture that has revolutionised NLP: Transformers. Understand the mechanism of self-attention and positional encoding that enables effective processing of sequential data.
  • Exploring Mixtral, GPT4, Claude and other Models: Analyse and compare the capabilities of various large language models like Mixtral. Evaluate their design, strengths, and potential use cases in the industry.
  • Navigating Regulations in AI Projects: Key compliance considerations.
  • Discovering the actual cost of adopting AI: Exploring the real cost of the adoption of AI.
  • Before Launching into Production: Essential Pre-Production Considerations.
  • Workshop 1: Explore and present a real-world application of generative AI, discussing its impact and underlying technology.
  • Workshop 2: Create a simple neural network using TensorFlow and present your results on a dataset of choice.
  • Workshop 3: Implement a small Transformer model to perform sentiment analysis on a dataset.
  • Workshop 4: Write a comparative analysis of the text generated by two different LLMsfor the same prompt.
  • Workshop 5: Apply the knowledge and skills acquired to develop your AI project.
  • Project: Crafting your AI project roadmap



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All basic CRM features
Up to 10,000 contacts
Normal support
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10 users included ($9/extra user)



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Up to 50,000 contacts
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All enterprise CRM features
Up to 200,000 contacts
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Account manager
200 users included ($5/extra user)

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