BeginnerArtificial Intelligence8 Weeks

Certificate IncludedCertificate EligibleVerified Learning Credential

Introduction to AI: Your First Step into Artificial Intelligence

An introduction to AI, machine learning, and neural networks covering Python essentials, computer vision, NLP, ethics, and a hands on capstone project.

Instructor / Mentor

Admin

Level & Duration

Beginner - 8 Weeks

Certificate Eligibility

Included / eligible

Pricing / Access Model

Paid course access - Paid - INR 14,500.00

Modules

Lessons

Curriculum preview

Take your first step into the exciting world of Artificial Intelligence with this introductory course from Ucanly. Designed for absolute beginners with no prior experience, this program demystifies AI, machine learning, and neural networks, teaching you the fundamentals from the ground up using Python to build your very first intelligent models. With Ucanly's supportive, hands on approach, you will discover the difference between AI and machine learning, understand how machines learn from data, and explore fascinating fields like Computer Vision and Natural Language Processing. The course focuses on intuition and practical experience, so you will grasp the core ideas without getting lost in complex math. By the end, you will have built several hands on AI projects, like a simple image classifier and a basic chatbot, and completed a final capstone project to showcase your new skills.

Module 1

Foundations of AI

Builds the foundations of AI: what it is, how it differs from machine learning and deep learning, where it shows up in everyday life, and setting up your Python environment.

1. What is Artificial Intelligence

2. AI vs Machine Learning vs Deep Learning

3. AI in Everyday Life

4. Setting Up Your Python Environment

Module 2

Python and Data Tools for AI

Covers the core Python data tools used throughout the course: Jupyter Notebooks, Pandas for handling data, NumPy for numerical computing, and basic data visualization.

1. Getting Started with Jupyter Notebooks

2. Working with Data using Pandas

3. Numerical Computing with NumPy

4. Visualizing Data

Module 3

Machine Learning Fundamentals

Introduces machine learning fundamentals, including supervised and unsupervised learning, linear regression, classification, and a hands on end to end regression project.

1. Introduction to Supervised Learning

2. Introduction to Unsupervised Learning

3. Linear Regression

4. Classification

Module 4

Neural Networks

Explores neural networks from the ground up: how they are structured, how they learn, building one with Keras, training and evaluation, and a hands on MNIST digit classification project.

1. Introduction to Neural Networks

2. How Neural Networks Learn

3. Building a Neural Network with Keras

4. Training and Evaluating Your Model

Module 5

Computer Vision

Covers Computer Vision, including how computers interpret images, convolutional neural networks, and a hands on project building an image classifier.

1. Introduction to Computer Vision

2. How Computers See Images

3. Convolutional Neural Networks (CNNs)

4. Hands On Project: Building an Image Classifier

Module 6

Natural Language Processing

Introduces Natural Language Processing, covering how text is represented numerically and a hands on sentiment analysis project.

1. Introduction to NLP

2. Representing Text as Numbers

3. Hands On Project: Sentiment Analysis

Module 7

AI Ethics and the Future

Covers AI ethics and responsible AI, including bias and fairness, responsible AI principles, and where the field of AI is headed next.

1. Bias and Fairness in AI

2. Responsible AI

3. The Future of AI

Module 8

Capstone Project

Guides you through the final capstone project, from choosing a direction and preparing data to building, training, and presenting your own AI project.

1. Choosing Your Capstone Direction

2. Planning and Data Preparation

3. Building and Training Your Model

4. Presenting Your Capstone