AI Agents

AI Agents: Build Smart & Automated AI Systems

AI Agent Course

AI Agents are currently a booming word in the IT industry. Learning an AI Agents course is going to be significant for your career. The 2 components of the term ‘AI Agents’ can give us a better understanding of it. AI or Artificial Intelligence means non-biological forms of intelligence built using computers and machines that can perform tasks that typically require human cognition, such as learning, problem-solving, decision-making, etc. The term ‘agent’ simply refers to a person who acts on behalf of another person, or an organization to achieve a goal. Combining these two terms, the AI Agent is an autonomous entity aware of its environment that can process information and take action to achieve specific goals. Streaming platforms like Netflix use learning AI agents to provide personalized content. They analyze user behavior, watch history, genre, viewing time, etc. to understand preferences.

An AI Agent can perform self-determined tasks to meet predetermined goals set by humans. They can process vast amounts of data, learn from interactions, and act independently. AI agents are reshaping the IT job market by automating repetitive tasks, enabling smart decision-making, and optimizing workflows. They will replace some traditional jobs, but they will also create new job opportunities. To become an AI Agent developer, you require programming skills, AI knowledge, and expertise in automation tools. Python is one of the widely used languages in AI development. Skills in machine learning models, neural networks, and NLP (Natural Language Processing) are necessary to build AI applications. You must also be proficient in API integrations, database management, and cloud-based AI services to become an AI developer. IT professionals can future-proof their careers by acquiring these skills in the growing AI landscape.

AI Agent

AI Agents

AI Agent Course in Kerala

AI Agent Courses

Our AI Agents course is a comprehensive program that covers everything from Python programming to building AI-powered automation tools. Python basics, data structures, object-oriented programming, etc. will be covered in the beginning and will progress into data science, machine learning, and deep learning. Then we will deep dive into NLP and AI agents. The course also covers LLMs, LangChain, prompt engineering, and API-based AI integration. You will also learn low-code AI automation tools such as n8n to build AI-driven workflows as part of the curriculum. Our AI agent training program is available both offline and online, offering students flexible ways to acquire these high-demand career development skills.

AI Agents

AI Agents Development Course

Document

Week 01

Week 01

Python Basics and Data Structures

Python installation, environment setup, and Jupyter Notebook.
Operators, functions, loops, and conditionals.
Data structures: Lists, Tuples, Sets, and Dictionaries.
File handling (text, CSV, JSON) and modular programming.

Week 02

Week 02

Python OOP, Exception Handling & JSON

Object-Oriented Programming (Classes, Objects, Methods)
Exception handling and debugging techniques.
Python Modules, Packages, and File Handling.
Working with JSON: Parsing and Serialization.

Week 03

Week 03

Python for Data Science & Exploratory Data Analysis (EDA)

Introduction to NumPy & Pandas.
Data manipulation and preprocessing with Pandas.
Data visualization techniques and plotting.
Cleaning and analyzing real-world datasets.

Week 04

Week 04

Machine Learning Algorithms (Part 1)

Introduction to Supervised Learning: Regression & Classification.
Linear & Multiple Linear Regression models.
Classification models: Logistic Regression, Decision Trees, Random Forest.
Model evaluation: Accuracy, Precision, and Recall.

Week 05

Week 05

Machine Learning Algorithms (Part 2)

Unsupervised Learning: Clustering (K-Means, Hierarchical).
Dimensionality Reduction techniques (PCA).
Introduction to Reinforcement Learning.
Implementing clustering & PCA using Scikit-Learn.

Week 06

Week 06

Introduction to Deep Learning & Neural Networks

Basics of Neural Networks and Deep Learning.
Introduction to TensorFlow and Keras.
Building and training a simple Neural Network.
Evaluating deep learning models.

Week 07

Week 07

Natural Language Processing (NLP) & Transformers

NLP Fundamentals: Tokenization, Stemming, Lemmatization.
Word Embeddings: Word2Vec, BERT.
Introduction to Transformers: GPT, BERT, LLaMA.
Using Hugging Face Transformers for NLP tasks.

Week 08

Week 08

Introduction to AI Agents

What are AI Agents and their types (Reactive, Proactive, Learning, Multi-Agent)?.
Using LLMs for AI Agents.
Fine-tuning vs API-based approaches.
Memory & context management in AI conversations.

Week 09

Week 09

LangChain & API-based AI Agents

Prompt Engineering: Zero-shot & Few-shot learning.
Chain-of-thought prompting and advanced techniques.
LangChain framework for AI workflows.
OpenAI function calling & Hugging Face models integration.

Week 10

Week 10

Low-Code AI Automation

Introduction to Low-Code AI Agents.
n8n interface and workflow automation.
Automating email responses and customer interactions.
Building Telegram chatbots with AI.

Week 11 & 12

Week 11 & 12

Capstone Project – AI-Powered Automation

Choose a final project (AI chatbot, email automation, etc.).
Developing and testing AI-powered applications.
Presenting live demos and showcasing project work.
Career guidance and next steps in AI development.
Week 01
Python Basics & Data Structures
Python installation, environment setup, and Jupyter Notebook.
Operators, functions, loops, and conditionals.
Data structures: Lists, Tuples, Sets, and Dictionaries.
File handling (text, CSV, JSON) and modular programming.
Week 02
Python OOP, Exception Handling & JSON
Object-Oriented Programming (Classes, Objects, Methods)
Exception handling and debugging techniques.
Python Modules, Packages, and File Handling.
Working with JSON: Parsing and Serialization.
Week 03
Python for Data Science & Exploratory Data Analysis (EDA)
Introduction to NumPy & Pandas.
Data manipulation and preprocessing with Pandas.
Data visualization techniques and plotting.
Cleaning and analyzing real-world datasets.
Week 04
Machine Learning Algorithms (Part 1)
Introduction to Supervised Learning: Regression & Classification.
Linear & Multiple Linear Regression models.
Classification models: Logistic Regression, Decision Trees, Random Forest.
Model evaluation: Accuracy, Precision, and Recall.
Week 05
Machine Learning Algorithms (Part 2)
Unsupervised Learning: Clustering (K-Means, Hierarchical).
Dimensionality Reduction techniques (PCA).
Introduction to Reinforcement Learning.
Implementing clustering & PCA using Scikit-Learn.
Week 06
Introduction to Deep Learning & Neural Networks
Basics of Neural Networks and Deep Learning.
Introduction to TensorFlow and Keras.
Building and training a simple Neural Network.
Evaluating deep learning models.
Week 07
Natural Language Processing (NLP) & Transformers
NLP Fundamentals: Tokenization, Stemming, Lemmatization.
Word Embeddings: Word2Vec, BERT.
Introduction to Transformers: GPT, BERT, LLaMA.
Using Hugging Face Transformers for NLP tasks.
Week 08
Introduction to AI Agents
What are AI Agents and their types (Reactive, Proactive, Learning, Multi-Agent)?.
Using LLMs for AI Agents.
Fine-tuning vs API-based approaches.
Memory & context management in AI conversations.
Week 09
LangChain & API-based AI Agents
Prompt Engineering: Zero-shot & Few-shot learning.
Chain-of-thought prompting and advanced techniques.
LangChain framework for AI workflows.
OpenAI function calling & Hugging Face models integration.
Week 10
Low-Code AI Automation
Introduction to Low-Code AI Agents.
n8n interface and workflow automation.
Automating email responses and customer interactions.
Building Telegram chatbots with AI.
Week 11 & 12
Capstone Project – AI-Powered Automation
Choose a final project (AI chatbot, email automation, etc.).
Developing and testing AI-powered applications.
Presenting live demos and showcasing project work.
Career guidance and next steps in AI development.

AI Agents

Why GALTech?

Classes from Industry Experts

Project-based

Job-focused

Placement Assistance

Internship Programs

HD Video Recordings

Weekly Projects & Assignments

Industry-specific Curriculum

Peer-to-peer

Self-paced

Certification

Affordable Fees

AI Agents

Who can join?

Graduates

Students who have completed their science degree (BSc, MSc, etc.) and want to build expertise in AI.

Professional Graduates

Those with degrees like BTech, BE, MTech, MCA, or a Diploma in CS/IT who want to enter the AI domain.

Working Professionals

Software engineers, data analysts, and IT professionals looking to switch careers or enhance their AI skill sets.

Common Queries

Frequently Asked Questions

The AI Agents course runs for 3 months, with 2.5 months of training on AI, ML, NLP, and automation. The last 2 weeks focus on a hands-on project to apply your skills.

You will receive an Internship Certification and a Course Completion Certification.

No prior experience is required. The course begins with Python fundamentals and gradually progresses to Machine Learning, AI Agents, and Automation.

Yes, You’ll build real-world AI projects like chatbots, automation workflows, and LLM-based apps. The last 2 weeks focus on a capstone project to apply your skills.

Yes, the course is offered in both online and offline formats to provide flexibility for students.

Graduates can pursue roles such as AI Engineer, AI Automation Specialist, Data Scientist, NLP Engineer, and AI Chatbot Developer.

You’ll receive mentorship from industry experts, hands-on project guidance, and career support to help you apply your skills effectively.

AI agents are widely used in customer support chatbots, AI-powered recommendation systems, workflow automation, and intelligent virtual assistants.

Yes! You’ll learn API-based AI integration, working with OpenAI & Hugging Face models, and automating workflows using LangChain and n8n.

This course goes beyond AI/ML concepts by focusing on AI agents, LLMs, automation, and real-world AI deployment, making it highly practical.

AI Agents

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