AI Engineering Training is a comprehensive program designed to equip participants with the skills and knowledge necessary to excel in the rapidly evolving field of Artificial Intelligence (AI). This training covers fundamental concepts, advanced methodologies, and practical applications of AI engineering, empowering participants to develop intelligent systems and deploy AI solutions across various domains.

javascript training

Course Features

Course Syllabus

Introduction to AI Engineering

Definition and history of AI

AI applications and domains

AI engineering process and lifecycle

Machine Learning Fundamentals

Introduction to supervised, unsupervised, and reinforcement learning

Linear regression and logistic regression

Model evaluation and validation techniques

Deep Learning Basics

Neural network architecture and components

Training neural networks

Introduction to TensorFlow/Keras for deep learning

Advanced Deep Learning

Convolutional neural networks (CNNs) for computer vision

Recurrent neural networks (RNNs) for sequence modeling

Transfer learning and fine-tuning pre-trained models

Natural Language Processing (NLP)

Text preprocessing and feature extraction

Word embeddings (Word2Vec, GloVe)

Sequence-to-sequence models and attention mechanisms

Computer Vision

Image preprocessing and augmentation

Object detection and localization

Image segmentation techniques

Ethical Considerations in AI

Bias and fairness in AI algorithms

Privacy and security concerns

AI regulation and policy

AI Engineering Tools and Frameworks

Overview of popular AI libraries and frameworks (TensorFlow, PyTorch)

Hands-on exercises with AI development tools

AI Deployment and Scalability

Deployment strategies for AI models (cloud, edge)

Scalability considerations and techniques

Monitoring and maintenance of deployed AI systems

Capstone Project

Real-world AI engineering project

Design, implementation, and evaluation of an AI solution

Presentation and documentation of project outcomes

Create your free Account