Veda IT

Who Should Join AI Course?

Job Switchers
Working Professionals
Engineering Graduates
University Students
Entry-Level Candidates

Keyskills of AI Developer

A Certificate Program in Artificial Intelligence equips individuals with essential skills such as a strong foundation in programming languages like Python or R and a solid understanding of mathematics, including linear algebra, calculus, and statistics. Key skills include proficiency in machine learning techniques, deep learning frameworks (e.g., TensorFlow, PyTorch), and data preprocessing.

Key Features

Covers machine learning, deep learning, NLP, and computer vision.
Real-world projects and exercises to develop practical AI skills.
Learn from experienced AI professionals and data scientists.
Offline classes with optional online support.
Recognized certificate from Veda IT upon successful course completion.

What you'll learn

The Certificate Program in Artificial Intelligence (AI) at Veda IT is a comprehensive course designed to introduce students to the field of AI, equipping them with foundational skills in machine learning, deep learning, natural language processing, and computer vision. This program is ideal for IT professionals, data enthusiasts, and students who want to explore AI technologies and understand how to apply AI algorithms to real-world problems. Through project-based learning and hands-on labs, students will gain practical experience in AI model building, data analysis, and algorithm implementation using popular tools and libraries like Python, TensorFlow, and Keras.

Throughout the course, students will explore supervised and unsupervised learning, neural networks, NLP, and computer vision. By the end of the program, graduates will be prepared for roles in AI development, data science, machine learning engineering, or further studies in advanced AI applications and research.

Modules Covered

Overview of AI and Its Applications
Setting Up Python and AI Libraries (TensorFlow, Keras)
Supervised vs. Unsupervised Learning
Data Preprocessing and Feature Engineering
Linear Regression, Logistic Regression, and K-Nearest Neighbors
Basic Classification and Clustering Techniques
Mini Project: Predictive Model for Classification Problem

Introduction to Neural Networks and Deep Learning
Understanding Perceptrons and Multi-Layer Networks
Building Deep Neural Networks with TensorFlow and Keras
Activation Functions, Optimizers, and Loss Functions
Convolutional Neural Networks (CNN) for Image Processing
Recurrent Neural Networks (RNN) for Sequential Data
Mini Project: Image Classification with CNN

Basics of NLP and Text Preprocessing
Working with Text Data (Tokenization, Stemming, Lemmatization)
Word Embeddings and Sentiment Analysis
Introduction to Transformers and BERT
Computer Vision Techniques (Image Filtering, Edge Detection)
Object Detection and Face Recognition
Mini Project: Sentiment Analysis or Object Detection Application

Machine Learning and Deep Learning Fundamentals
Neural Network Architecture Design
NLP and Computer Vision Techniques
Model Evaluation, Tuning, and Deployment
Hands-On Experience with AI Libraries (TensorFlow, Keras, Scikit-Learn)
Data Preprocessing and Feature Engineering
AI Model Deployment and Cloud Integration

Learning Path

Introduction to AI and Machine Learning Basics

Learn the fundamentals of Artificial Intelligence, Machine Learning concepts, and key algorithms.

Deep Learning and Neural Networks

Explore deep learning techniques and build neural networks using frameworks like TensorFlow or PyTorch.

Natural Language Processing (NLP) and Computer Vision

Work on text data analysis with NLP and image processing with computer vision techniques.

Model Deployment and AI Ethics

Deploy AI models for real-world applications while understanding ethical considerations in AI development.

Mini Projects for Hands-On Experience

Apply your AI skills through small-scale, practical projects to reinforce your learning.

Capstone Project and Career Guidance

Develop an end-to-end AI project and gain expert career advice to excel in the AI industry.

Potential Roles

AI Developer
Machine Learning Engineer
Data Scientist (AI-Focused)
NLP Engineer
Computer Vision Specialist
AI Research Assistant
AI Product Developer

Start Date20/05/2025
Enrolled100
Lectures50
Skill LevelBasic
LanguageEnglish,Telugu
Quizzes10
CertificateYes
Pass Percentage100%

Certificate Program in Artificial Intelligence (AI)

Upon successful completion of the Certificate Program in Artificial Intelligence, you will receive a certificate from Veda IT, validating your skills in AI development, model deployment, and advanced data analysis.

Enroll Now

Design and Developed by Colourmoon

AI

Who Should Join AI Course?

Job Switchers

Working Professionals

Engineering Graduates

University Students

Entry-Level Candidates

Keyskills of AI Developer

Key Features

What you'll learn

Modules Covered

Module 1: Introduction to AI and Machine Learning Basics 3 hours

Module 2: Deep Learning and Neural Networks 3 hours

Module 3: Natural Language Processing (NLP) and Computer Vision 3 hours

Module 4: Model Deployment and AI Ethics 3 hours

Learning Path

Potential Roles

Certificate Program in Artificial Intelligence (AI)