Master Artificial Intelligence & Build Intelligent Solutions
Explore the world of Artificial Intelligence through Python, Machine Learning, Deep Learning, Natural Language Processing and Generative AI. Learn how intelligent systems work and develop practical AI applications through guided projects.
Understand the foundations of AI, intelligent systems and their applications.
Explore algorithms, model training and evaluation using real datasets.
Learn about LLMs, prompting, embeddings and modern AI applications.
Build hands-on AI projects to apply technical concepts.
Understand AI. Learn the Technology Behind Intelligent Systems.
Artificial Intelligence is transforming
how organizations analyze information,
automate processes and build digital products.
This course introduces Python for AI,
Machine Learning fundamentals,
neural networks, Natural Language Processing
and Generative AI concepts.
Learn how to prepare datasets,
train and evaluate models,
understand large language models
and build introductory AI-powered
applications through practical exercises.
Artificial Intelligence Skills You'll Develop
Explore the foundations and practical applications of modern AI technologies.
Python for Artificial Intelligence
Learn Python programming, NumPy, Pandas and data processing fundamentals for AI development.
Machine Learning
Understand supervised and unsupervised learning, model training, prediction and evaluation.
Deep Learning
Explore neural networks, activation functions, backpropagation and introductory deep learning.
Natural Language Processing
Learn text preprocessing, sentiment analysis, embeddings and language processing concepts.
Generative AI & LLMs
Understand prompting, transformers, large language models and retrieval-augmented generation.
AI Application Development
Explore AI APIs, model integration, introductory AI agents and responsible AI practices.
AI Tools & Technologies You'll Explore
Become familiar with popular tools, libraries and concepts used in AI workflows.
Artificial Intelligence Course Syllabus
A structured roadmap from AI fundamentals to practical Machine Learning and Generative AI applications.
Module 01 — Introduction to Artificial Intelligence
- What is Artificial Intelligence?
- AI vs Machine Learning vs Deep Learning
- Types and applications of AI
- Introduction to Generative AI
- AI development workflow
- Responsible AI and common limitations
Module 02 — Python Programming for AI
- Python setup and Jupyter Notebook
- Variables, data types and operators
- Conditional statements and loops
- Functions and modules
- Lists, tuples and dictionaries
- NumPy and Pandas fundamentals
- Data loading and preparation
Module 03 — Mathematics & Data Preparation
- Linear algebra fundamentals
- Statistics and probability basics
- Understanding datasets
- Handling missing values
- Feature scaling and encoding
- Train, validation and test splits
- Exploratory Data Analysis
Module 04 — Machine Learning Fundamentals
- Supervised vs unsupervised learning
- Linear and logistic regression
- Decision trees and random forests
- K-nearest neighbors
- Clustering fundamentals
- Model training with Scikit-learn
- Overfitting and underfitting
- Model evaluation metrics
Module 05 — Deep Learning & Neural Networks
- Introduction to neural networks
- Neurons, layers and activation functions
- Forward propagation and backpropagation
- Loss functions and optimizers
- Introduction to TensorFlow and Keras
- Training a basic neural network
- Convolutional neural network concepts
Module 06 — Natural Language Processing
- Introduction to NLP
- Text cleaning and tokenization
- Stop words and lemmatization
- Bag-of-words and TF-IDF
- Sentiment analysis
- Text classification
- Introduction to word embeddings
Module 07 — Generative AI & Large Language Models
- What is Generative AI?
- Transformer architecture overview
- Introduction to LLMs
- Tokens and context windows
- Prompt engineering techniques
- Working with model APIs
- Understanding hallucinations and model limitations
Module 08 — RAG & AI Agents
- Introduction to embeddings
- Vector search fundamentals
- Retrieval-Augmented Generation
- Document-based question answering
- Introduction to AI agents
- Tool calling and workflow concepts
- Basic agent safety and evaluation
Module 09 — AI Application Development
- Building an AI-powered application
- Using AI APIs with Python
- Basic chatbot architecture
- Model input and output handling
- Introduction to Streamlit
- Model deployment fundamentals
- Testing and evaluating AI outputs
- Privacy and security considerations
Module 10 — Capstone Projects & Portfolio
- Selecting an AI project problem
- Collecting and preparing data
- Building and testing a model
- Developing a simple AI application
- Evaluating model performance
- Documenting limitations
- Organizing code on GitHub
- Final project presentation
Build Practical AI Projects
Apply AI concepts through realistic project exercises involving prediction, text analysis and Generative AI.
AI-Powered Prediction Model
Prepare a dataset, train a Machine Learning model, evaluate performance and visualize prediction results.
Sentiment Analysis Application
Build a basic NLP application that classifies customer reviews or feedback into sentiment categories.
Generative AI Document Assistant
Create a document-based question-answering prototype using an LLM API, embeddings and retrieval.
Develop Skills for AI & Machine Learning Careers.
AI technologies are used in
software development, analytics,
automation, customer support,
research and intelligent applications.
Python, Machine Learning,
NLP and Generative AI knowledge
can support several technical
career paths.
Advanced AI roles generally
require additional expertise
in mathematics, programming,
model development and deployment.
Questions About Artificial Intelligence
Can beginners learn Artificial Intelligence?
Is Python included in the AI course?
Does the course cover Machine Learning?
Will I learn Generative AI and ChatGPT-related concepts?
Are practical AI projects included?
Is mathematics important for AI?
Ready to Explore Artificial Intelligence?
Explore Artificial Intelligence training with Placify India and develop practical skills in Python, Machine Learning, NLP, Generative AI and intelligent application development.