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Note - SPPU's Degreeplus Beta Version is up, stay tuned for more details.
For Course Creators
For Students
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AI for Data Science
Home Skillsoft AI for Data Science

Course

AI for Data Science

45 hours, 53 minutes 22 Seconds

Description

AI along with generative AI is a cutting-edge technology that will transform nearly every
business function, ranging from content creation and product design, to improving customer experience and marketing new ideas.  While the benefits of AI are immense, technology has its limitations and poses some ethical considerations.  In this Journey designed for front-line learners, you will be introduced to AI concepts and ethical considerations.

What Students Will Learn

  • Skill Benchmark: AI Landscape Literacy (Beginner Level)
  • Course: An Introduction to Generative AI Concepts
  • Course: Generative Modeling Foundations
  • Course: Getting Started with Large Language Models (LLMs)
  • Course: Exploring the Depths of Large Language Models in Generative AI
  • Course: Leveraging Generative AI for Business
  • Course: Artificial Intelligence and Machine Learning
  • Course: Deep Learning and Neural Networks
  • Course: An Introduction to GPT Models
  • Course: Considerations for using AI Responsibly

  • Skill Benchmark: NLP with Deep Learning Competency (Intermediate)
  • Generative AI Models: Getting Started with autoencoders
  • Generative AI Models: Generating Data Using Variational Autoencoders
  • Generative AI Models: Generating Data Using Generative Adversarial Networks
  • NLP Using Deep Learning
  • Using Recurrent Networks for NLP
  • Using Out-of-the-box Transformer Models for NLP
  • Attention-based Models and Transformers for NLP
  • Transformers: The “T” in the GPT
  • Interactive Course: Exploring Transformers with Hugging face
  • Lab: Exploring Transformers and their Carbon footprint

  • Skill Benchmark: NLP and LLMs Competency (Intermediate)
  • Course: NLP with LLM: Working with Tokenizers in Hugging Face
  • Course: NLP with LLMs: Hugging Face Classification, QnA, & Text Generation Pipelines
  • Course: NLP with LLMs: Language Translation, Summarization, & Semantic Similarity
  • Course: NLP with LLMs: Fine-tuning Models for Classification & Question Answering
  • Course: Introduction to Finetuning
  • Interactive Course: Finetuning Transformers with Hugging Face
  • Lab: Finetuning Language Models: Practice Lab
  • Course: RAG Foundations
  • Course: Build a RAG App
  • Interactive Course RAG Techniques
  • Course: NLP with LLMs: Fine-tuning Models for Language Translation, & Summarization

  • AI for Data Science: Bookshelf

Overall Learning Outcomes

  1. Foundational Understanding: Build a strong foundation in generative AI, deep learning, and LLMs.
  2. Practical Skills: Learn to implement, fine-tune, and evaluate advanced AI and NLP models using cutting-edge tools like Hugging Face.
  3. Ethical Awareness: Gain awareness of ethical considerations and environmental impacts of AI technologies..
  4. Business Applications: Learn to leverage AI for business functions such as content creation, data
    generation, and customer engagement.

By the end of the course, students are equipped to understand, implement, and optimize generative AI and NLP models for real-world applications.

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