Learn AI with Python

This Python AI course is an introduction to artificial intelligence (AI), an encouragement to build a smart environment, and a route to hands-on experience. 

(AI-PYTHON.AW1) / आईएसबीएन : 978-1-64459-677-7
Lessons
Lab
TestPrep
AI Tutor (ऐड ऑन)
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इस कोर्स के बारे में

Enroll in our Python AI course and build intelligent applications that interact with the world around you. 

In this course, dive into AI programming with Python, from setting up your AI environment to implementing neural networks, NLP, and speech recognition. Master machine learning (ML) algorithms for classification, regression, and clustering. Then apply them to real-world problems. 

Learn to construct AI agents, automate tasks with logic programming, and even build object recognition models using Convolutional Neural Networks (CNNs).

कौशल जो आपको प्राप्त होंगे

  • Build & Deploy AI Models: Create machine learning and deep learning applications using Python.
  • ML Algorithms: Implement classification, regression, and clustering for real-world problem-solving.
  • Neural Networks Development: Design and train ANNs (Artificial Neural Networks) and CNNs for image recognition.
  • NLP Automation: Process and analyze text using Natural Language Processing (NLTK) techniques like tokenization and sentiment analysis.
  • Speech Recognition: Build AI systems that understand and respond to spoken language.
  • Reinforcement Learning: Develop intelligent agents that learn from environments using Python.
  • AI Solutions Optimization: Fine-tune models with performance metrics, regularization, and advanced architectures like YOLO and R-CNN.

1

Preface

2

Introduction to AI and Python

  • Introduction
  • Introduction to Artificial Intelligence (AI)
  • Why to learn AI?
  • Understanding intelligence
  • Various fields of study in AI
  • Applications of AI in various industries
  • How does artificial intelligence learn?
  • AI agents and environments
  • AI and Python – how do they relate?
  • Python3 - installation and setup
  • Conclusion
  • Questions
3

Machine Learning and Its Algorithms

  • Introduction
  • Understanding Machine Learning (ML)
  • The Landscape of Machine Learning Algorithms
  • Components of a Machine Learning algorithm
  • Different learning styles in machine learning algorithms
  • Popular machine learning algorithms
  • Questions
4

Classification and Regression Using Supervised Learning

  • Introduction
  • Classification
  • Various steps to build a classifier using Python
  • Lazy learning versus eager learning
  • Performance metrics for classification
  • Regression
  • Various steps to build a regressor using Python
  • Performance metrics for regression
  • Conclusion
  • Questions
5

Clustering Using Unsupervised Learning

  • Introduction
  • Clustering
  • Various methods to form clusters
  • Important ML clustering algorithms
  • Conclusion
  • Questions
6

Solving Problems with Logic Programming

  • Introduction
  • Logic programming
  • Building blocks of logic programming
  • Useful Python packages for logic programming
  • Implementation examples
  • Conclusion
  • Questions
7

Natural Language Processing with Python

  • Introduction
  • Natural Language Processing (NLP)
  • Installing Python's NLTK Package
  • Understanding tokenization, stemming, and lemmatization
  • Understanding chunking
  • Understanding Bag-of-Words (BoW) model
  • Understanding stop words
  • Understanding vectorization and transformers
  • Some examples
  • Conclusion
8

Implementing Speech Recognition with Python

  • Introduction
  • Basics of speech recognition
  • Building a speech recognizer
  • Conclusion
  • Questions
9

Implementing Artificial Neural Network (ANN) with Python

  • Introduction
  • Understanding of Artificial Neural Network (ANN)
  • Optimizers for training the neural network
  • Regularization
  • Installing useful Python package for ANN
  • Examples of building some neural networks
  • Conclusion
  • Questions
10

Implementing Reinforcement Learning with Python

  • Understanding reinforcement learning
  • Markov Decision Process (MDP)
  • Building blocks of reinforcement learning
  • Constructing an environment using Python
  • Constructing an agent using Python
  • Conclusion
  • Questions
11

Implementing Deep Learning and Convolutional Neural Network

  • Introduction
  • Understanding Deep Learning
  • Elucidation of Convolutional Neural Networks
  • The Architecture of Convolutional Neural Network
  • Localization and object recognition with deep learning
  • Image classification using CNN in Python
  • Conclusion
  • Questions

कोई प्रश्न? FAQ देखें

  Want to Learn More?

हमसे अभी संपर्क करें

  • AI mimics human intelligence (e.g., chatbots).
  • ML (a subset of AI) uses algorithms to learn from data (e.g., spam filters).
  • Deep Learning (a subset of ML) uses neural networks for complex tasks (e.g., image recognition). Python libraries like TensorFlow simplify the implementation.

Yes, but with realistic expectations. A structured 3-month Python AI course (10–20 hours/week) can help you grasp foundational AI concepts, Python programming, and basic machine learning (ML) algorithms. 

However, mastering advanced topics like deep learning or NLP typically requires longer practice. 

Absolutely. Python is the top language for AI due to its simplicity and rich libraries (e.g., TensorFlow, PyTorch, scikit-learn). Most of our courses, such as Learn AI with Python or Building Machine Learning Systems using Python, use Python for hands-on projects in ML, neural networks, and NLP.

No. This AI coding in Python course requires no prior knowledge as it teaches Python basics alongside AI concepts. 

Roles include AI Developer ($130K avg salary), ML Engineer, Data Scientist, or NLP Specialist. Projects like building image classifiers or chatbots boost employability.

Key Python tools:

  • NumPy/pandas: Data manipulation
  • TensorFlow/PyTorch: Neural networks
  • NLTK: NLP tasks

Projects often use Jupyter Notebooks for prototyping.

Future-Proof Your Skills

  The only Python AI course that won’t put you to sleep (promise).

$279.99

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