Title: Introduction to AI

Location: US

Company: Arm Education

About this course:
Are you curious about how artificial intelligence (AI) really works? Wondering which models power these systems, and how they impact society and the environment? Presented by engineers from Arm, this course offers a comprehensive introduction to AI, machine learning, and data science—shedding light on their historical evolution, current capabilities, and potential future developments.
By exploring both the technical concepts and the broader ethical, social, and environmental dilemmas, you will gain a well-rounded understanding of AI’s potential and challenges. You’ll discover how AI, machine learning, and data science interrelate; understand the fundamental algorithms, models, and frameworks; and learn how to apply these concepts in real-world scenarios. The course also addresses the pressing issue of energy consumption in AI.
Key Topics Covered

The turbulent history of AI and its evolution into today’s powerful technology

How AI, machine learning, and data science fit together , including their definitions, examples, and interrelationship

Current and potential future applications of AI in various industries

Fundamental machine learning concepts , including classifiers, linear regression, and neural networks

Training, validation, and test data : how to prepare and evaluate machine learning models

Optimizers and loss functions : building blocks for fine-tuning your models

Ethical and social considerations : exploring AI’s benefits, challenges, and the importance of responsible development

Power consumption vs. sustainability : balancing performance and efficiency with environmental impact

Practical frameworks , such as PyTorch, for implementing and training ML models

AI in the cloud and on the edge : deploying AI across diverse platforms and computing environments

The course culminates with a hands-on capstone project using the PyTorch framework and the CIFAR-10 dataset, allowing you to apply newly acquired skills to a real-world image classification challenge. Whether you’re a budding data scientist, a developer looking to integrate AI into your projects, or simply an AI enthusiast, this course offers both the foundational knowledge and practical skills needed to excel in the rapidly evolving world of artificial intelligence.

You will:

Define AI, machine learning, and data science, as well as build knowledge of examples and uses of each.

Explore the interrelationships between AI, machine learning, and data science.

Build understanding of the benefits and challenges of AI, including the ethical and social issues involved.

Examine a range of neural networks, ML models, and ML frameworks, and explore their applications (including training).

Explore the discussion around balancing power consumption and sustainability.

Apply the skills and knowledge you have gained across the course to build, train, and run your own ML classification model.

Discover the fundamental concepts behind artificial intelligence (AI) and machine learning in this introductory course. Explore the various types of AI, examine ethical considerations, and delve into the key machine learning models that power modern AI systems. Whether your goal is to work directly with AI, strengthen your software development skills, or enhance your data science expertise, this course provides an essential foundation for success in the field.

Duration: 12 weeks

Skills:
- Algorithms
- Artificial Intelligence
- Balancing (Ledger/Billing)
- Contextual Image Classification
- Curiosity
- Data Science
- Energy Consumption
- Keys And Locks
- Linear Regression
- Machine Learning
- PyTorch (Machine Learning Library)
- Software Development

Curriculum:
- Module 1: Introduction to Artificial Intelligence
- Module 2: AI and Machine Learning
- Module 3: What's in the Black Box? Deep Learning and Neural Networks
- Module 4: Training and Evaluating Models
- Module 5: Advanced Topics in AI

- Module 6: Challenges and the Future of AI