🤖 AI & Machine Learning

AI Development Tools and Frameworks

This course provides a comprehensive exploration of the essential tools and frameworks used in AI development. It is des...

885

Views

🤖

Sections

1. Introduction to AI Development
18 views

An overview of AI development, its importance, and key considerations.

10 topics (10 versions)

1.1Definition of AI Development

1.2Historical Background

1.3AI vs. Machine Learning

1.4Applications of AI

1.5Challenges in AI Development

1.6AI Development Lifecycle

1.7Ethical Considerations in AI

1.8AI Trends and Future Directions

1.9Introduction to AI Tools

1.10Selecting the Right Framework

2. Setting Up Your AI Development Environment
13 views

Guidelines for configuring a productive AI development environment.

10 topics (10 versions)

2.1Hardware Requirements

2.2Operating System Considerations

2.3Installing Python and R

2.4Setting Up IDEs

2.5Version Control Systems

2.6Using Virtual Environments

2.7Cloud Computing for AI

2.8Containerization with Docker

2.9GPU vs CPU Processing

2.10Managing Dependencies

3. Data Management and Preprocessing
18 views

Strategies for effective data management and preprocessing in AI projects.

10 topics (10 versions)

3.1Understanding Data Types

3.2Data Collection Techniques

3.3Data Cleaning and Wrangling

3.4Feature Engineering

3.5Data Normalization and Scaling

3.6Handling Imbalanced Data

3.7Data Augmentation Techniques

3.8Data Annotation Tools

3.9Data Storage Solutions

3.10Big Data Technologies

4. Introduction to AI Frameworks
16 views

An introduction to popular AI frameworks and their applications.

10 topics (10 versions)

4.1TensorFlow Overview

4.2PyTorch Overview

4.3Keras Overview

4.4Scikit-Learn Overview

4.5Caffe Overview

4.6MXNet Overview

4.7Theano Overview

4.8ONNX Overview

4.9Apache Spark for AI

4.10Framework Selection Criteria

5. Deep Learning with TensorFlow
14 views

Building and deploying deep learning models using TensorFlow.

10 topics (10 versions)

5.1Installing TensorFlow

5.2TensorFlow Basics

5.3Building Neural Networks

5.4Training and Evaluation

5.5TensorFlow Datasets

5.6Model Optimization

5.7Deploying TensorFlow Models

5.8Using TensorBoard

5.9TensorFlow Serving

5.10TensorFlow Lite and TensorFlow.js

6. Machine Learning with Scikit-Learn
18 views

Implementing machine learning models using Scikit-Learn.

10 topics (10 versions)

6.1Installing Scikit-Learn

6.2Scikit-Learn Basics

6.3Supervised Learning Models

6.4Unsupervised Learning Models

6.5Model Evaluation Metrics

6.6Hyperparameter Tuning

6.7Pipeline and Model Persistence

6.8Cross-Validation Techniques

6.9Ensemble Methods

6.10Deploying Scikit-Learn Models

7. Natural Language Processing with NLP Libraries
14 views

Leveraging NLP libraries for processing and analyzing text data.

10 topics (10 versions)

7.1Introduction to NLP

7.2Text Preprocessing Techniques

7.3Sentiment Analysis

7.4Named Entity Recognition

7.5Topic Modeling

7.6Text Classification

7.7Word Embeddings

7.8Using SpaCy

7.9Using NLTK

7.10Transformers and BERT

8. Computer Vision with OpenCV and Other Tools
8 views

Techniques and tools for building computer vision applications.

10 topics (10 versions)

8.1Introduction to Computer Vision

8.2Image Processing with OpenCV

8.3Object Detection Techniques

8.4Image Segmentation

8.5Facial Recognition

8.6Augmented Reality

8.7Using TensorFlow for Vision

8.8Using PyTorch for Vision

8.9Deployment of Vision Models

8.10Real-time Image Processing

9. Reinforcement Learning Frameworks
10 views

Methods and frameworks for developing reinforcement learning models.

10 topics (10 versions)

9.1Introduction to Reinforcement Learning

9.2Understanding Markov Decision Processes

9.3Q-Learning and Deep Q-Networks

9.4Policy Gradient Methods

9.5Using OpenAI Gym

9.6Distributed RL Frameworks

9.7Model-free vs Model-based RL

9.8Case Studies in RL

9.9Challenges in RL

9.10Future Trends in RL

10. AI Model Deployment and Monitoring
11 views

Best practices for deploying and monitoring AI models.

10 topics (10 versions)

10.1Model Deployment Strategies

10.2Using Docker for Deployment

10.3Monitoring Model Performance

10.4Model Versioning and Management

10.5A/B Testing for AI Models

10.6Continuous Integration and Deployment

10.7Scalability Considerations

10.8Security in AI Deployments

10.9Ethical Monitoring of AI Models

10.10Real-time Inference

11. AI in the Cloud
9 views

Leveraging cloud platforms for AI development and deployment.

10 topics (10 versions)

11.1Introduction to Cloud AI Services

11.2AWS AI and ML Services

11.3Google Cloud AI Platform

11.4Azure Machine Learning

11.5IBM Watson AI Services

11.6Cost Management in Cloud AI

11.7Cloud vs On-premises AI

11.8Security in Cloud AI

11.9Hybrid Cloud Solutions

11.10Serverless AI Functions

12. Ethics and Governance in AI
8 views

Exploring the ethical implications and governance frameworks in AI.

10 topics (10 versions)

12.1Introduction to AI Ethics

12.2Data Privacy Concerns

12.3Bias and Fairness in AI

12.4Transparency and Explainability

12.5Regulatory Compliance

12.6AI Governance Frameworks

12.7Responsible AI Development

12.8Impact of AI on Society

12.9Ethical AI Case Studies

12.10Future Directions in AI Ethics

13. Advanced AI Techniques and Research
13 views

Exploration of cutting-edge AI techniques and ongoing research.

10 topics (10 versions)

13.1Introduction to Advanced AI Techniques

13.2Transfer Learning

13.3Generative Adversarial Networks (GANs)

13.4Federated Learning

13.5Edge AI

13.6Quantum Machine Learning

13.7Explainable AI

13.8Neural Architecture Search

13.9AI for Scientific Research

13.10AI in Healthcare

Earn your certificate

Sign in to track your progress

When you’re signed in, we’ll remember which sections you’ve viewed. Finish all sections and you’ll unlock a downloadable certificate to keep or share.

🤖 AI & Machine Learning

AI Development Tools and Frameworks

This course provides a comprehensive exploration of the essential tools and frameworks used in AI development. It is des...

885

Views

🤖

Sections

1. Introduction to AI Development
18 views

An overview of AI development, its importance, and key considerations.

10 topics (10 versions)

1.1Definition of AI Development

1.2Historical Background

1.3AI vs. Machine Learning

1.4Applications of AI

1.5Challenges in AI Development

1.6AI Development Lifecycle

1.7Ethical Considerations in AI

1.8AI Trends and Future Directions

1.9Introduction to AI Tools

1.10Selecting the Right Framework

2. Setting Up Your AI Development Environment
13 views

Guidelines for configuring a productive AI development environment.

10 topics (10 versions)

2.1Hardware Requirements

2.2Operating System Considerations

2.3Installing Python and R

2.4Setting Up IDEs

2.5Version Control Systems

2.6Using Virtual Environments

2.7Cloud Computing for AI

2.8Containerization with Docker

2.9GPU vs CPU Processing

2.10Managing Dependencies

3. Data Management and Preprocessing
18 views

Strategies for effective data management and preprocessing in AI projects.

10 topics (10 versions)

3.1Understanding Data Types

3.2Data Collection Techniques

3.3Data Cleaning and Wrangling

3.4Feature Engineering

3.5Data Normalization and Scaling

3.6Handling Imbalanced Data

3.7Data Augmentation Techniques

3.8Data Annotation Tools

3.9Data Storage Solutions

3.10Big Data Technologies

4. Introduction to AI Frameworks
16 views

An introduction to popular AI frameworks and their applications.

10 topics (10 versions)

4.1TensorFlow Overview

4.2PyTorch Overview

4.3Keras Overview

4.4Scikit-Learn Overview

4.5Caffe Overview

4.6MXNet Overview

4.7Theano Overview

4.8ONNX Overview

4.9Apache Spark for AI

4.10Framework Selection Criteria

5. Deep Learning with TensorFlow
14 views

Building and deploying deep learning models using TensorFlow.

10 topics (10 versions)

5.1Installing TensorFlow

5.2TensorFlow Basics

5.3Building Neural Networks

5.4Training and Evaluation

5.5TensorFlow Datasets

5.6Model Optimization

5.7Deploying TensorFlow Models

5.8Using TensorBoard

5.9TensorFlow Serving

5.10TensorFlow Lite and TensorFlow.js

6. Machine Learning with Scikit-Learn
18 views

Implementing machine learning models using Scikit-Learn.

10 topics (10 versions)

6.1Installing Scikit-Learn

6.2Scikit-Learn Basics

6.3Supervised Learning Models

6.4Unsupervised Learning Models

6.5Model Evaluation Metrics

6.6Hyperparameter Tuning

6.7Pipeline and Model Persistence

6.8Cross-Validation Techniques

6.9Ensemble Methods

6.10Deploying Scikit-Learn Models

7. Natural Language Processing with NLP Libraries
14 views

Leveraging NLP libraries for processing and analyzing text data.

10 topics (10 versions)

7.1Introduction to NLP

7.2Text Preprocessing Techniques

7.3Sentiment Analysis

7.4Named Entity Recognition

7.5Topic Modeling

7.6Text Classification

7.7Word Embeddings

7.8Using SpaCy

7.9Using NLTK

7.10Transformers and BERT

8. Computer Vision with OpenCV and Other Tools
8 views

Techniques and tools for building computer vision applications.

10 topics (10 versions)

8.1Introduction to Computer Vision

8.2Image Processing with OpenCV

8.3Object Detection Techniques

8.4Image Segmentation

8.5Facial Recognition

8.6Augmented Reality

8.7Using TensorFlow for Vision

8.8Using PyTorch for Vision

8.9Deployment of Vision Models

8.10Real-time Image Processing

9. Reinforcement Learning Frameworks
10 views

Methods and frameworks for developing reinforcement learning models.

10 topics (10 versions)

9.1Introduction to Reinforcement Learning

9.2Understanding Markov Decision Processes

9.3Q-Learning and Deep Q-Networks

9.4Policy Gradient Methods

9.5Using OpenAI Gym

9.6Distributed RL Frameworks

9.7Model-free vs Model-based RL

9.8Case Studies in RL

9.9Challenges in RL

9.10Future Trends in RL

10. AI Model Deployment and Monitoring
11 views

Best practices for deploying and monitoring AI models.

10 topics (10 versions)

10.1Model Deployment Strategies

10.2Using Docker for Deployment

10.3Monitoring Model Performance

10.4Model Versioning and Management

10.5A/B Testing for AI Models

10.6Continuous Integration and Deployment

10.7Scalability Considerations

10.8Security in AI Deployments

10.9Ethical Monitoring of AI Models

10.10Real-time Inference

11. AI in the Cloud
9 views

Leveraging cloud platforms for AI development and deployment.

10 topics (10 versions)

11.1Introduction to Cloud AI Services

11.2AWS AI and ML Services

11.3Google Cloud AI Platform

11.4Azure Machine Learning

11.5IBM Watson AI Services

11.6Cost Management in Cloud AI

11.7Cloud vs On-premises AI

11.8Security in Cloud AI

11.9Hybrid Cloud Solutions

11.10Serverless AI Functions

12. Ethics and Governance in AI
8 views

Exploring the ethical implications and governance frameworks in AI.

10 topics (10 versions)

12.1Introduction to AI Ethics

12.2Data Privacy Concerns

12.3Bias and Fairness in AI

12.4Transparency and Explainability

12.5Regulatory Compliance

12.6AI Governance Frameworks

12.7Responsible AI Development

12.8Impact of AI on Society

12.9Ethical AI Case Studies

12.10Future Directions in AI Ethics

13. Advanced AI Techniques and Research
13 views

Exploration of cutting-edge AI techniques and ongoing research.

10 topics (10 versions)

13.1Introduction to Advanced AI Techniques

13.2Transfer Learning

13.3Generative Adversarial Networks (GANs)

13.4Federated Learning

13.5Edge AI

13.6Quantum Machine Learning

13.7Explainable AI

13.8Neural Architecture Search

13.9AI for Scientific Research

13.10AI in Healthcare

Earn your certificate

Sign in to track your progress

When you’re signed in, we’ll remember which sections you’ve viewed. Finish all sections and you’ll unlock a downloadable certificate to keep or share.

AI Development Tools and Frameworks

Sections

1. Introduction to AI Development18 views

2. Setting Up Your AI Development Environment13 views

3. Data Management and Preprocessing18 views

4. Introduction to AI Frameworks16 views

5. Deep Learning with TensorFlow14 views

6. Machine Learning with Scikit-Learn18 views

7. Natural Language Processing with NLP Libraries14 views

8. Computer Vision with OpenCV and Other Tools8 views

9. Reinforcement Learning Frameworks10 views

10. AI Model Deployment and Monitoring11 views

11. AI in the Cloud9 views

12. Ethics and Governance in AI8 views

13. Advanced AI Techniques and Research13 views

Sign in to track your progress

AI Development Tools and Frameworks

Sections

1. Introduction to AI Development18 views

2. Setting Up Your AI Development Environment13 views

3. Data Management and Preprocessing18 views

4. Introduction to AI Frameworks16 views

5. Deep Learning with TensorFlow14 views

6. Machine Learning with Scikit-Learn18 views

7. Natural Language Processing with NLP Libraries14 views

8. Computer Vision with OpenCV and Other Tools8 views

9. Reinforcement Learning Frameworks10 views

10. AI Model Deployment and Monitoring11 views

11. AI in the Cloud9 views

12. Ethics and Governance in AI8 views

13. Advanced AI Techniques and Research13 views

Sign in to track your progress

1. Introduction to AI Development
18 views

2. Setting Up Your AI Development Environment
13 views

3. Data Management and Preprocessing
18 views

4. Introduction to AI Frameworks
16 views

5. Deep Learning with TensorFlow
14 views

6. Machine Learning with Scikit-Learn
18 views

7. Natural Language Processing with NLP Libraries
14 views

8. Computer Vision with OpenCV and Other Tools
8 views

9. Reinforcement Learning Frameworks
10 views

10. AI Model Deployment and Monitoring
11 views

11. AI in the Cloud
9 views

12. Ethics and Governance in AI
8 views

13. Advanced AI Techniques and Research
13 views

1. Introduction to AI Development
18 views

2. Setting Up Your AI Development Environment
13 views

3. Data Management and Preprocessing
18 views

4. Introduction to AI Frameworks
16 views

5. Deep Learning with TensorFlow
14 views

6. Machine Learning with Scikit-Learn
18 views

7. Natural Language Processing with NLP Libraries
14 views

8. Computer Vision with OpenCV and Other Tools
8 views

9. Reinforcement Learning Frameworks
10 views

10. AI Model Deployment and Monitoring
11 views

11. AI in the Cloud
9 views

12. Ethics and Governance in AI
8 views

13. Advanced AI Techniques and Research
13 views