In today’s age, learning AI is crucial as companies increasingly rely on it for efficiency, automation, and personalization, yet not everyone is an expert in the field. Salesforce offers short courses on Trailhead, covering essential AI skills to help you become the AI hero your company needs, positioning you for new opportunities and career advancement. This article lists the top courses by Salesforce to help you gain expertise in AI and excel in your career.
Artificial Intelligence Fundamentals
This course covers AI fundamentals, including key concepts, challenges in defining AI, and tasks it can perform. It explains the differences between hand-coded algorithms and trained models, the relationship between machine learning and AI, and the impact of data types on training. It also explores neural networks, their components, and the complexity of deep learning.
Large Language Models
This course covers large language models (LLMs), their training, and fine-tuning. It helps you choose the right LLM for your business and understand the limitations of different LLM options.
Generative AI Basics
This course explores generative AI, its capabilities, and underlying technology. It covers key vocabulary, the tech stack, and rapid development components, as well as addressing common business concerns about generative AI.
Natural Language Processing Basics
This course covers the basics of natural language processing (NLP), its evolution, and everyday applications. It differentiates between NLP, natural language understanding, and generation and explains key techniques like sentiment, intent, and context analysis.
Einstein Classification Apps for Service
This course teaches how to use Einstein classification apps to enhance case data with predictive intelligence, saving support agents time. It covers preparing data, implementing the apps, adjusting prediction settings, and enabling agents to utilize Einstein’s recommendations.
Prompt Fundamentals
This course teaches how to write effective prompts for generative AI. It covers prompt design, creating prompt templates, adding CRM data to prompts, and iterating on the design process to improve content creation.
Model Fine-Tuning
This course covers the benefits, mechanics, and challenges of fine-tuning large language models. It explains when to use fine-tuning and how to prepare datasets, and it provides an overview of the fine-tuning process.
Generative AI for Images
This course teaches techniques for creating high-quality images with AI, highlighting the advantages of diffusion models over GANs. It covers popular generative AI tools, setting realistic goals, creating effective prompts, and addressing ethical concerns of AI-generated artwork.
Responsible Creation of Artificial Intelligence
This course covers creating ethical AI systems by removing bias from data and algorithms. It teaches defining bias and fairness, building diverse teams, aligning design with company values, understanding ethical vs. legal standards, and implementing best practices to identify and mitigate ethical risks in AI development.
Critical Thinking and Decision-Making with Data and AI
This course covers strategies for enhancing decision-making with data and AI, including critical thinking, data-driven decision-making, and AI integration. It teaches questioning techniques, decision-making models, real-world applications, and ethical considerations across various industries.
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