Mastering Ai: Basics To Aws Certified Ai Practitioner
Published 7/2025
Created by Banking and Finance School
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Level: All | Genre: eLearning | Language: English | Duration: 57 Lectures ( 5h 32m ) | Size: 3.7 GB
Unlock the future with AI - from foundational concepts to practical AWS deployment in one comprehensive course.
What you'll learn
History, ethics, and societal implications of AI
Core AI concepts: logic, reasoning, search, probability
Machine learning techniques: supervised, unsupervised, reinforcement learning
Deep learning architectures including CNNs, RNNs, and generative models
Practical implementation of AI with AWS services like SageMaker, Lex, Polly, Rekognition
Preparation for AWS Certified AI Practitioner exam
Real-world case studies and ethical AI deployment strategies
Requirements
Basic understanding of mathematics (algebra, probability, statistics)
Familiarity with programming (preferably Python)
Interest in AI/ML concepts and technologies
No prior AI experience required - this course starts from scratch
Description
Artificial Intelligence (AI) is transforming the world at an unprecedented pace - revolutionizing industries, reshaping how we work, and unlocking powerful tools that once existed only in science fiction. This course is your gateway to becoming a confident AI practitioner. Whether you're a student, developer, or business professional, you'll gain a solid foundation in AI, machine learning, deep learning, and AWS-based AI services, preparing you for real-world implementation and certification.Section 1: Introduction to Artificial IntelligenceThis section lays the groundwork for understanding AI by exploring its definition and historical evolution. You'll learn how AI evolved from rule-based systems to modern-day intelligent agents. We then highlight AI's growing importance and diverse applications - from healthcare to finance to autonomous vehicles. The section concludes with a thoughtful discussion on AI ethics, societal impact, and the moral responsibilities of building intelligent systems.Section 2: Foundations of Artificial IntelligenceHere, we dive into the core building blocks of AI. Beginning with an overview, you'll study logic and reasoning systems that enable machines to make decisions. You'll then explore probability and statistics as a backbone for uncertainty handling in AI. Important AI problem-solving strategies like search algorithms are introduced, followed by knowledge representation and reasoning - enabling machines to 'think' and 'understand' their environment.Section 3: Machine Learning in Artificial IntelligenceMachine Learning (ML) is a core component of modern AI. This section starts with an introduction to ML and delves into supervised and unsupervised learning paradigms. Concepts such as clustering, distance metrics, and dimensionality reduction are explained with real-world analogies. We also explore association rule learning, reinforcement learning, and its types. By the end, you'll understand how machines learn from data and improve over time.Section 4: Deep LearningDeep learning powers today's most advanced AI applications. This section begins with the basics of neural networks, followed by an introduction to deep learning architectures. You'll gain insights into CNNs used for image recognition, RNNs used for sequential data, and generative models for AI creativity. Topics like transfer learning and fine-tuning are also covered to show how pre-trained models can be leveraged for better performance.Section 5: AWS Certified AI PractitionerThis final section prepares students for AWS AI certification and practical industry applications. It starts with a comprehensive introduction to AWS AI and ML tools, such as SageMaker, DeepLens, Lex, Polly, and Rekognition. Students will learn to build, train, and deploy models using AWS infrastructure. We also explore AI services in NLP and computer vision, model evaluation, ethical AI development, prompt engineering, and best practices. The section includes case studies, exam prep, and continuous improvement strategies to reinforce learning.Conclusion:By the end of this course, you'll not only understand the theoretical foundations of AI but also gain hands-on experience with powerful tools used by industry professionals. Whether you're looking to apply AI in business, pursue a technical career, or pass the AWS Certified AI Practitioner exam, this course equips you with the knowledge and confidence to move forward.
Who this course is for
Students and professionals seeking a career in AI and machine learning
Data scientists and developers wanting AWS certification
Business leaders and product managers exploring AI implementation
Educators and researchers aiming to understand or teach AI fundamentals
Anyone curious about how AI works and how to use it responsibly and effectively
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