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**BaDshaH** · 09-06-2023, 01:25 AM

[Image: 148171f7346ed3457ecbf794536e3564.jpg]

Published 9/2023
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz
Language: English | Size: 6.12 GB | Duration: 12h 41m

Your Complete Guide to Artificial Intelligence

[b]What you'll learn[/b]
Students will develop a solid understanding of the definition and historical evolution of AI.
Students will see how AI technologies are transforming industries and solving complex problems.
Students will explore the responsibilities associated with AI technologies, including topics like bias, fairness, transparency, and privacy.
This course will equip students with essential machine learning skills, including supervised learning techniques for prediction and classification.
Students will gain a comprehensive understanding of deep learning, including the principles and techniques behind artificial neural networks.
Students will learn how feedforward neural networks work and how they can be used for various AI tasks.
Students will explore different activation functions used in neural networks and understand their role in modeling complex data.
Students will learn how CNNs are used for image recognition and processing.
Students will understand how RNNs can be applied to tasks involving sequences, such as natural language processing and time series analysis.
Students will engage in a hands-on capstone project. This project will require them to apply the concepts they have learned to solve real-world AI challenges.

[b]Requirements[/b]
Learners should be comfortable using a computer and common software applications.
While not mandatory, a basic understanding of algebra and problem-solving skills can be helpful in grasping some AI and machine learning concepts.
Familiarity with programming basics is beneficial, but the course will provide introductory materials for those with limited programming experience.
Participants should have access to a computer or laptop with an internet connection to access course materials, online resources, and programming tools.
A code editor or integrated development environment (IDE) for Python, such as Jupyter Notebook or Visual Studio Code, is recommended.
A modern web browser is necessary for accessing online resources and course materials.
The course is designed to be accessible to beginners, and participants will receive guidance and support to help them build the necessary skills and knowledge.

[b]Description[/b]
** Mastering Artificial Intelligence: Your Ultimate Guide to AI **Welcome to Selfcode Academy's comprehensive AI course! Whether you're a beginner or a seasoned tech enthusiast, this program is designed to empower you with the skills and knowledge needed to excel in the exciting world of Artificial Intelligence.Who Can Benefit:Beginners: No prior AI experience required! This course is perfect for those embarking on their AI journey.Students: Whether you're in high school, college, or pursuing graduate studies, this course complements your academic pursuits.Professionals: Looking to boost your career prospects? Transitioning to AI from another field? No problem! This course is tailored for you.Tech Innovators: Entrepreneurs and visionaries, get ready to turn your AI concepts into reality.Data Enthusiasts: If you're passionate about data and want to harness its potential with AI, this course is your gateway.Lifelong Learners: Stay updated with the latest AI advancements and become part of the tech-savvy community.Course Highlights:Module 1: Introduction to AIDefine AI and uncover its fascinating history.Explore AI's impact in healthcare, finance, and various industries.Delve into crucial ethical considerations in AI.Module 2: Machine Learning FundamentalsLearn to make predictions and categorize data through supervised learning.Discover patterns in unlabeled data using unsupervised learning.Evaluate model performance using essential metrics like accuracy, precision, and recall.Module 3: Deep Learning and Neural NetworksGrasp the intricacies of artificial neural networks (ANNs).Dive into feedforward neural networks, activation functions, and their applications.Get hands-on experience with convolutional and recurrent neural networks (CNNs and RNNs).Module 4: Natural Language Processing (NLP)Prepare text data for analysis with advanced preprocessing techniques.Perform sentiment analysis and text classification.Generate coherent text using cutting-edge AI models.Module 5: Computer VisionMaster image processing techniques and feature extraction.Detect objects and segment images effectively.Leverage CNNs for image classification.Module 6: Reinforcement LearningExplore the foundations of reinforcement learning and Markov Decision Processes (MDPs).Implement Q-learning and value iteration algorithms to solve complex problems.Module 7: Capstone ProjectApply your newfound AI expertise to solve real-world challenges.Embark on this thrilling AI adventure with us! Our hands-on projects, clear explanations, and supportive community will boost your confidence to tackle AI challenges and contribute to the future of technology. Start your journey to AI mastery today!* All the resource files are added in video 1 of section 1.

Overview
Section 1: 1. Introduction to Artificial Intelligence
Lecture 1 Introduction to AI
Lecture 2 History and Types of AI
Lecture 3 Application of AI
Lecture 4 Ethical Considerations in AI
Section 2: Machine Learning Fundamentals
Lecture 5 Machine Learning fundamentals
Lecture 6 ML Data Pre Processing-Lab session
Lecture 7 Evaluation Metrics
Lecture 8 Machine Learning Types & Supervised machine learning algorithms
Lecture 9 Model Based on Linear Regression- Lab Session
Lecture 10 Supervised machine learning algorithms
Lecture 11 Comparing Classification Algorithms
Lecture 12 Unsupervised learning
Lecture 13 K-Means clustering Model
Section 3: Deep learning
Lecture 14 Deep Learning and Neural Networks Introduction
Lecture 15 Deep Learning and Neural Networks Introduction Part-2
Lecture 16 Artificial Neural Networks Model
Lecture 17 Convolutional neural networks
Lecture 18 CNN for Image Classification
Lecture 19 Recurrent neural networks
Lecture 20 RNN Sun Spot Model
Section 4: 4. Natural Language Processing (NLP)
Lecture 21 Natural Language Processing Introduction
Lecture 22 Text Pre Processing
Lecture 23 Text Pre-processing Model
Lecture 24 Sentiment Analysis
Lecture 25 Language modeling and generation
Lecture 26 Sentiment analysis Model
Section 5: Computer Vision
Lecture 27 Computer Vision Introduction
Lecture 28 Image Processing
Lecture 29 Feature Extraction
Lecture 30 Object Detection
Lecture 31 Image Segmentation
Lecture 32 Image Segmentation Process & Image Classification
Lecture 33 Face Mask Detection Model
Section 6: Reinforcement Learning
Lecture 34 Introduction to Reinforcement learning
Lecture 35 Reinforcement Learning Algorithms
Lecture 36 Reinforcement Learning Model
Section 7: Capstone Project
Lecture 37 Capstone Project -Heart Disease Prediction Model
Beginners in AI: Individuals who are entirely new to the field of AI and want to explore its fundamental concepts and practical applications will benefit from this course. We provide a solid foundation for those with no prior experience.,Students: High school students, college undergraduates, and postgraduates pursuing degrees in computer science, data science, engineering, or related fields can use this course to supplement their academic knowledge and gain hands-on experience in AI.,Professionals Seeking Career Advancement: Working professionals looking to transition into AI-related roles or enhance their existing skill set will find this course valuable. It provides practical insights and hands-on experience applicable to various industries.,Entrepreneurs and Innovators: Individuals interested in creating AI-powered solutions, startups, or tech innovations will gain a strong foundation in AI concepts and techniques to bring their ideas to life.,Data Enthusiasts: Anyone passionate about data analysis, machine learning, or data-driven decision-making can use this course to acquire the skills needed to work with AI and machine learning technologies.,AI Enthusiasts: Those with a general interest in AI, robotics, and automation can satisfy their curiosity by gaining a comprehensive understanding of AI's principles and real-world applications.,Lifelong Learners: Individuals who are lifelong learners eager to explore cutting-edge technologies and stay up-to-date with the latest advancements in AI and machine learning will find this course engaging and informative.,This course is designed to be inclusive, with content structured to accommodate learners at different levels of expertise. Whether you're a complete novice or someone looking to deepen your knowledge in AI, our course provides a flexible learning path to meet your needs and interests.

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