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AI+ Engineer™ Self-Paced Learning V3
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Datos del curso
General
Course Introduction
Lab Instructions
Audio Book: Introduction AI+ Engineer
Module 1: Foundations of Artificial Intelligence (AI)
Module 1: Foundations of Artificial Intelligence
Audio Book: Foundations of Artificial Intelligence
Podcast: Foundations of Artificial Intelligence
1.1 Historical Perspective
ACTIVITY: Drag and Drop
1.2 Machine Learning Fundamentals
1.3 Introduction to Deep Learning
1.4 Data: The Fuel of AI
ACTIVITY: Hotspot
1.5 Bias, Fairness, Transparency, and Accountability
ACTIVITY: Tab
ACTIVITY: Knowledge Check
Quiz
Lab Practice 1.1
Lab Practice 1.2
Lab Practice 1.3
Python File Download
Module 2: Introduction to Architecture
Module 2: Introduction to AI Architecture
Audio Book: Introduction to AI Architecture
Podcast: Introduction to AI Architecture
2.1 Contemporary Applications Across Industries
ACTIVITY: Hotspot
2.2 Key Components and Structures
2.3 Role in Solving Real-World Problems
2.3.1 Setting up a Basic AI Environment
ACTIVITY: Drag and Drop
2.4 Phases: Planning, Data Collection, Model Building, Deployment, and Monitoring
2.5 Best Practices in Each Phase of AI Development
2.5.1 Guided installation and configuration of AI frameworks.
ACTIVITY: Timeline
ACTIVITY: Tab
ACTIVITY: Knowledge Check
Quiz
Lab Practice 2.1
Lab Practice 2.2
Python File Download
Module 3: Fundamentals of Neural Networks
Module 3: Fundamentals of Neural Networks
Audio Book: Fundamentals of Neural Networks
Podcast: Fundamentals of Neural Networks
3.1 Neurons, Layers, and Architectures
3.2 Feedforward and Backpropagation Concepts
3.2.1 Building a Simple Neural Network for Handwritten Digit Recognition
ACTIVITY: Hotspot
3.3 Common Activation Functions
3.4 Importance of Activation Functions in Shaping the Netwrok's Behavior
3.4.1 Train and evaluate the neural network on a MNIST Dataset
ACTIVITY: Drag and Drop
3.5 Understanding the Backpropagation Process
3.6 Popular Optimization Algorithms (Gradient Descent, Adam, RMSprop)
3.6.1 Predictions with the Model on TEXT Data
ACTIVITY: Timeline
ACTIVITY: Tab
ACTIVITY: Knowledge Check
Quiz
Lab Practice 3.1
Python File Download
Module 4: Applications of Neural Networks
Module 4: Applications of Neural Networks
Audio Book: Applications of Neural Networks
Podcast: Applications of Neural Networks
4.1 Understanding How Neural Networks Process Images
4.2 Real-world Applications in Image Recognition and Computer Vision
ACTIVITY: Hotspot
4.3 Introduction to Handling Sequential Data Using Neural Networks
4.3.1 Build a CNN to classify handwritten digits from the MNIST dataset.
4.4 Applications in Natural Language Processing and Time Series Analysis
4.4.1 Build a Recurrent Neural Network (RNN) to classify movie reviews as positive or negative sentiment using the IMDB dataset.
ACTIVITY: Drag and Drop
4.5 Utilizing Transfer Learning with Pre-Trained Models for Practical Applications
4.5.1 Image Classification with VGG16
ACTIVITY: Tab
ACTIVITY: Knowledge Check
Quiz
Lab Practice 4.1
Lab Practice 4.2
Lab Practice 4.3
Lab Practice 4.4
Lab Practice 4.5
Lab Practice 4.6
Python File Download
Module 5: Significance of Large Language Modules(LLM)
Module 5: Significance of Large Language Models (LLM)
Audio Book: Significance of Large Language Models (LLM)
Podcast: Significance of Large Language Models (LLM)
5.1 How do LLMs Work?
5.2 Understanding the Function of LLMs in Natural Language Comprehension
5.3 Implications for Various Practical Applications
ACTIVITY: Hotspot
5.4 Overview of Widely Used Large Language Models (BERT, GPT, and Others)
5.4.1 Pre-trained GPT-2 language model for generating text
5.5 Unique Features and Use Cases in Real-world Scenarios
ACTIVITY: Drag and Drop
5.6 Adapting Pre-trained Models for Domain-specific Tasks
5.7 Techniques for Effective Finetuning of Language Models
5.7.1 Practical Fine-tuning for Text Classification across Diverse Applications
ACTIVITY: Tab
ACTIVITY: True or False
ACTIVITY: Knowledge Check
Quiz
Lab Practice 5.1
Lab Practice 5.2
Lab Practice 5.3
Lab Practice 5.4
Lab Practice 5.5
Lab Practice 5.6
Lab Practice 5.7
Lab Practice 5.8
Lab Practice 5.9
Python File Download
Module 6: Application of Generative AI
Module 6: Application of Generative AI
Audio Book: Application of Generative AI
Podcast: Application of Generative AI
6.1 Understanding the Basic Concept and Structure of GANs
6.2 Real-world Applications in Image Generation and Data Augmentation
6.2.1 Real-world Implementation of a GAN for Image Generation
ACTIVITY: Hotspot
6.3 Understanding VAEs and Their Applications for Generative Tasks
6.4 Use Cases in Image Synthesis and Data Representation
ACTIVITY: Drag and Drop
6.5 Practical Techniques for Creating Synthetic Data
6.6 Addressing Challenges Related to Data Scarcity in Practical Scenarios
6.6.1 Training and Evaluating the Model on Practical Datasets
ACTIVITY: True or False
ACTIVITY: Timeline
ACTIVITY: Knowledge Check
Quiz
Lab Practice 6.1
Python File Download
Module 7: Natural Language Processing
Module 7: Natural Language Processing
Audio Book: Natural Language Processing
Podcast: Natural Language Processing
7.1 Practical Applications of NLP in Various Industries
7.2 Real-world Scenarios in Sentiment Analysis, Chatbots, and Language Translation
7.2.1 Implementation of Sentiment Analysis (SA)
7.2.2 Implementation of Machine Learning Approach for SA
7.2.3 Implementation of Deep learning Approach for SA
7.2.4 Developing a functional Chatbot using natural language processing and machine learning techniques
ACTIVITY: Tab
7.3 Attention Mechanism
7.3.1 Explores the Attention Mechanism
7.3.2 Sample python code for Language Translation
7.3.3 Implementation of Machine Learning Approach for Language Translation
ACTIVITY: Pick One
7.4 Practical Insights into BERT (Bidirectional Encoder Representations from Transformers)
7.4.1 Implementation of BERT Model
7.4.2 Implementation of BERT model for IMDB Dataset
7.5 Real-world Applications in Various NLP Tasks
7.5.1 Implementing an End-to-End NLP Pipeline with a Practical Focus
7.5.2 Utilizing Hugging Face Transformers for Efficient and Practical NLP Solutions
ACTIVITY: True or False
ACTIVITY: Carousel
ACTIVITY: Knowledge Check
Quiz
Lab Practice 7.1
Lab Practice 7.2
Lab Practice 7.3
Lab Practice 7.4
Lab Practice 7.5
Lab Practice 7.6
Lab Practice 7.7
Lab Practice 7.8
Python File Download
Module 8: Transfer Learning with Hugging Face
Module 8: Transfer Learning with Hugging Face
Audio Book: Transfer Learning with Hugging Face
Podcast: Transfer Learning with Hugging Face
8.1 Principles and Advantages of Transfer Learning
8.2 Applications in Various Domains
8.2.1 Implementing Transfer Learning with Hugging Face Models for Various Tasks
8.2.2 Sentiment Analysis Without Transformers
8.2.3 Sentiment Analysis in Just 2 Lines Of Code Using Transformers
ACTIVITY: Sequence Arrangement
8.3 Different Approaches to Transfer Learning
8.4 Choosing the Right Strategy for Specific Tasks
8.4.1 Code for Custom Object Recognition Task Using a Pre-trained Model
8.4.2 Code for sentiment analysis on a custom dataset using Hugging Transformer:
ACTIVITY: Tab
ACTIVITY: Pick One
ACTIVITY: Knowledge Check
Quiz
Lab Practice 8.1
Lab Practice 8.2
Lab Practice 8.3
Lab Practice 8.4
Python File Download
Module 9: Crafting Sophisticated GUIs for AI Solutions
Module 9: Crafting Sophisticated GUIs for AI Solutions
Audio Book: Crafting Sophisticated GUIs for AI Solutions
Podcast: Crafting Sophisticated GUIs for AI Solutions
9.1 Importance of User-Friendly Interfaces
9.2 Various Ways for Implementing GUI
ACTIVITY: Multiple Select
9.3 Streamlit: A Python Library for Interactive Web Applications
9.3.1 Streamlit: A Python Library for Interactive Web Applications
9.4 Dash (Plotly): Creating Interactive Web-based Dashboards with Python
9.4.1 Dash (Plotly): Creating Interactive Web-based Dashboards with Python
ACTIVITY: Hotspot
9.5 Tkinter (Python): Standard GUI Library for Python
9.5.1 Tkinter (Python): Standard GUI Library for Python
9.6 PyQt and PySide (Python): Python Bindings for the Qt Framework
9.6.1 PyQt and PySide (Python): Python Bindings for the Qt Framework
9.7 Electron (JavaScript, HTML, CSS): Cross-platform Desktop Applications
ACTIVITY: Pick One
ACTIVITY: Knowledge Check
Quiz
Lab Practice 9.1
Lab Practice 9.2
Lab Practice 9.3
Python File Download
Module 10: AI Communication and Deployment Pipeline
Module 10: AI Communication and Deployment Pipeline
Audio Book: AI Communication and Deployment Pipeline
Podcast: AI Communication and Deployment Pipeline
10.1 Strategies for Clear and Concise Communication
10.2 Visualizations and Storytelling with AI Results
ACTIVITY: True or False
10.3 Key Components of a Robust Deployment Pipeline
10.4 Continuous Integration and Continuous Deployment (CI/CD) Practices
ACTIVITY: Sequence Arrangement
10.5 Understanding Client Needs and Expectations
10.6 Prototyping Approaches and Methodologies
ACTIVITY: Drag and Drop
ACTIVITY: Pick One
ACTIVITY: Knowledge Check
Quiz
Lab Practice 10.1
Python File Download
Additional Module - AI Agents For Engineer
AI Agent Engineer
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AI CERTs Exam Guidelines
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Información del curso
AI+ Engineer™ Self-Paced Learning V3
Skill Level
:
Beginner
certificate name
:
AI+ Engineer™
Badge
:
Badge-AI+-Engineer.png
Course Layout
:
Standard
