Mastering Artificial Intelligence
Your Complete Guide to Artificial Intelligence
Artificial Intelligence,Machine Learning,Deep Learning
Lectures -37
Resources -3
Duration -12.5 hours
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Course Description
** 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 AI
Define 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 Fundamentals
Learn 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 Networks
Grasp 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 Vision
Master image processing techniques and feature extraction.
Detect objects and segment images effectively.
Leverage CNNs for image classification.
Module 6: Reinforcement Learning
Explore the foundations of reinforcement learning and Markov Decision Processes (MDPs).
Implement Q-learning and value iteration algorithms to solve complex problems.
Module 7: Capstone Project
Apply 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.********************
Goals
What will you learn in this course:
Course Goals:
Gain Comprehensive Understanding: Develop a comprehensive understanding of Artificial Intelligence (AI) by exploring its history, impact, and ethical considerations, empowering you to navigate the intricate world of AI technology.
Master Machine Learning Techniques: Acquire proficiency in essential machine learning techniques, including supervised and unsupervised learning, and effectively evaluate model performance through accurate metric analysis.
Grasp Deep Learning Concepts: Develop a strong grasp of deep learning and neural network concepts, including artificial neural networks, feedforward and recurrent neural networks, and their practical applications in various fields.
Harness Natural Language Processing (NLP): Acquire the skills to preprocess textual data, perform sentiment analysis, and comprehend advanced NLP concepts, enabling you to generate coherent text using cutting-edge AI models.
Excel in Computer Vision: Master image processing, object detection, and image segmentation techniques, and leverage convolutional neural networks (CNNs) for effective image classification, providing you with the ability to interpret and process visual data.
Explore Reinforcement Learning Principles: Gain an in-depth understanding of reinforcement learning and Markov Decision Processes (MDPs), and implement fundamental algorithms like Q-learning and value iteration, equipping you to solve complex problems with autonomous decision-making capabilities.
Apply Knowledge in Real-world Scenarios: Apply the acquired AI expertise to real-world challenges through the capstone project, enabling you to demonstrate your skills and contribute effectively to the advancement of AI technology in various industries.
Prerequisites
What are the prerequisites for this course?
Course Prerequisites:
Basic Programming Knowledge: Familiarity with at least one programming language such as Python, Java, or C++ is essential to comprehend and implement the coding concepts covered throughout the course.
Understanding of Mathematics and Statistics: A foundational understanding of mathematics, including algebra, calculus, and probability, as well as basic statistical concepts, will aid in grasping the fundamental principles underlying AI algorithms and models.
Familiarity with Data Handling: Prior experience in handling and analyzing datasets, along with an understanding of data structures and data manipulation techniques, will be beneficial for comprehending the various data-driven components of the AI course.
Proficiency in Computer Science Concepts: A basic understanding of computer science principles, including data structures, algorithms, and computational complexity, will facilitate the comprehension of advanced AI concepts and their practical implementations.
Familiarity with Basic Machine Learning Concepts: A foundational understanding of basic machine learning concepts, including supervised and unsupervised learning, will provide a solid foundation for comprehending more complex AI algorithms and models discussed throughout the course.
Eagerness to Learn and Experiment: An enthusiastic attitude towards learning, a willingness to experiment with new concepts and technologies, and a strong desire to delve deeper into the world of Artificial Intelligence will contribute significantly to your success in this course.
Curriculum
Check out the detailed breakdown of what’s inside the course
Introduction to Artificial Intelligence
4 Lectures
- Introduction to AI 17:20 17:20
- History and Types of AI 18:09 18:09
- Application of AI 14:07 14:07
- Ethical Considerations in AI 13:02 13:02
Machine Learning Fundamentals
9 Lectures
Deep learning
7 Lectures
Natural Language Processing (NLP)
6 Lectures
Computer Vision
7 Lectures
Reinforcement Learning
3 Lectures
Capstone Project
1 Lectures
Instructor Details
Selfcode Academy
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