The Introduction of AI and Machine Learning with Python

🤖 Welcome to The Introduction of AI and Machine Learning with Python at Fun Robotics Academy!

🚀 Course Headline: Learn Data Science, Machine Learning (Artificial Intelligence), Deep Learning & more from the absolute basics!

🔍 About This Course: Dive into the fascinating world of Artificial Intelligence (AI) and Machine Learning (ML) with our comprehensive online course. Designed for beginners to advanced learners, this course will guide you through the intricacies of AI, teaching you how to implement complex algorithms that can solve real-world problems. You'll learn the machine learning workflow from data pre-processing to model design and testing, and gain hands-on experience with Python, TensorFlow, and Keras.

By the end of this course, you will:

• Build AI models from scratch.
• Understand the principles behind complex concepts like Deep Learning and Computer Vision.
• Apply Machine Learning algorithms to real datasets, including customer segmentation, image recognition, and sentiment analysis.
• Explore various applications of NLP tasks.
• Master the tools needed to become an AI expert!

📚 Course Breakdown:

Unit 1: Introduction to Python for Data Science

• Learn Python programming basics.
• Understand data manipulation using pandas and numpy libraries.

Unit 2: Machine Learning Fundamentals

• Grasp the concepts of Supervised vs Unsupervised learning.
• Dive into classification and regression tasks.

Unit 3: Clustering Techniques

• Explore unsupervised learning through KMeans clustering.
• Discover the Elbow method for optimal clustering.

Unit 4: Customer Segmentation with Machine Learning

• Implement KMeans algorithm to segment customers.
• Analyze and target the right customer groups.

Unit 5: Market Basket Analysis

• Apply Apriori algorithm for association rule mining.
• Measure support, confidence, and lift.

Unit 6: Recommendation Systems

• Build both content-based and collaborative filtering recommendation systems.
• Understand user-based and item-based approaches.

Unit 7: Sentiment Analysis using NLP

• Tokenize text data for analysis.
• Create models to predict sentiment in reviews or comments.

Unit 8: Introduction to Deep Learning

• Understand the architecture of neural networks and deep neural networks.
• Process image data for machine learning.

Unit 9: Computer Vision with Pre-trained Models

• Learn about transfer learning with ResNet50.
• Classify images using pre-trained models.

Capstone Project:

• Apply the knowledge gained to a real-world project, showcasing your ability to implement AI techniques.

🎓 Who Is This Course For? This course is designed for:

• Aspiring data scientists and ML engineers.
• Software developers looking to expand their skillset with AI and ML.
• Students and professionals in STEM fields interested in AI applications.
• Anyone curious about how AI works and eager to build their own AI models!

🚀 What Will You Gain? By the end of this course, you'll have a solid understanding of AI and ML concepts and be equipped with the practical skills to apply these technologies to real-world problems. You'll also join a community of like-minded learners and professionals who are passionate about advancing in the field of AI.

📅 Start Your AI Journey Today! Enroll now and take your first step towards becoming an AI expert with Fun Robotics Academy's The Introduction of AI and Machine Learning with Python course. Let's embark on this exciting journey together to unlock the potential of AI in our world! 🌟