Unlock the power of Artificial Intelligence (AI) and Machine Learning (ML) in this hands-on, beginner-friendly course tailored for aspiring data scientists, developers, and tech enthusiasts. Learn how machines think, predict, and automate using Python programming and real-world datasets.
This AI and ML course in Python walks you through the complete journey from understanding basic concepts to building and deploying simple machine learning models using industry-standard tools like Jupyter Notebooks, Google Colab, NumPy, Pandas, TensorFlow, and Keras.
📘 What You’ll Learn:
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📌 What is AI and Machine Learning?
Understand the fundamentals of AI & ML with real-world applications. -
📌 Types of Machine Learning
Explore Supervised, Unsupervised, and Reinforcement Learning. -
📌 Python Basics for Data Science
Get hands-on with Python, data types, control structures, NumPy, and Pandas. -
📌 Data Preprocessing and Exploration
Learn data cleaning, handling missing values, outliers, and visualizing data using Matplotlib and Seaborn. -
📌 Supervised Learning
Build regression and classification models including Linear Regression, Logistic Regression, Decision Trees, and Random Forests. -
📌 Unsupervised Learning
Dive into K-means clustering, hierarchical clustering, and performance evaluation. -
📌 Neural Networks and Deep Learning
Understand and implement basic Neural Networks, CNNs for image processing, and RNNs for time series and text.
🛠️ Tools & Technologies Used:
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Python
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Jupyter Notebook
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Google Colab
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NumPy, Pandas
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Matplotlib, Seaborn
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Scikit-learn
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TensorFlow & Keras
🎯 Who This Course Is For:
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Beginners interested in AI and Machine Learning
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Students and professionals from engineering, computer science, or data science
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Anyone looking to start a career in AI/ML or Data Science
🌟 Why Join This Course?
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Beginner to Advanced Roadmap
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Hands-on Projects & Assignments
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Practice on Real-World Datasets
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Community Support & Continued Learning Resources
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Learn on Google Colab & Jupyter – No installation required!
Instructor
