AI & Python Development Megaclass: AI & Python — From Fundamentals to Deep Learning and Beyond

Vivian Aranha

$199.99

Video Sep 2025 57hrs 57mins 1st Edition

Vivian Aranha

$199.99

Video Sep 2025 57hrs 57mins 1st Edition

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Key benefits

Build strong foundations with Python basics, data structures, file handling, and clean coding practices
Apply data science techniques using NumPy, Pandas, and visualization libraries for analysis
Implement deep learning architectures including CNNs, RNNs, LSTMs, Transformers, and GANs

Description

This course begins with Python programming essentials, including control flow, functions, data structures, and file handling. You’ll then explore core data science tools such as NumPy for numerical computing, Pandas for data manipulation, and Matplotlib/Seaborn for data visualization. Mathematics foundations—linear algebra, calculus, probability, and statistics—are introduced to support AI learning. Each week ends with mini-projects to apply concepts. As you progress, you’ll dive into machine learning techniques, covering regression, classification, ensemble methods, feature engineering, and hyperparameter tuning. Advanced algorithms such as Random Forests, XGBoost, LightGBM, and CatBoost are explored. Deep learning modules guide you through building neural networks, CNNs for image recognition, RNNs and LSTMs for sequence tasks, and Transformers for NLP applications. The final stages emphasize hands-on projects and real-world deployment. You’ll apply skills in computer vision, NLP, reinforcement learning, and time series forecasting. GANs expand your understanding of generative modeling, while AI in production introduces Docker, CI/CD, and cloud scaling. The course concludes with modules on AI ethics, safety, and governance, ensuring responsible and practical AI expertise.

Who is this book for?

This course is designed for aspiring AI developers, data scientists, and software engineers who want an end-to-end pathway in AI with Python. It suits learners seeking to strengthen programming, mathematics, and data science foundations before diving into machine learning and deep learning. Professionals aiming to build expertise in NLP, computer vision, or reinforcement learning will benefit. Beginners with basic programming knowledge can start confidently. Experienced practitioners can deepen skills in advanced AI techniques and deployment practices.

What you will learn

Write Pythonic code and manage data using NumPy, Pandas, and Matplotlib
Design supervised, unsupervised, and ensemble machine learning algorithms
Construct deep learning models with TensorFlow, Keras, and PyTorch
Apply CNNs, RNNs, LSTMs, and Transformers to NLP and computer vision tasks
Generate data and solutions using GANs and reinforcement learning frameworks
Deploy secure, scalable AI systems in production while addressing ethics and governance

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