---
title: AI & Deep Learning with Python Certification | Amity Online
description: Enroll in AI and Deep Learning with Python certification. Gain hands-on experience in neural networks, deep learning models, and AI applications.
---

# Certificate in Artificial Intelligence and Deep learning using Python

Post successful completion, apply for paid internship

In Collaboration With

Embark on a transformative journey into AI and Deep Learning with a Certificate in Artificial Intelligence and Deep Learning using Python. Designed for professionals and enthusiasts alike, this program equips learners with hands-on expertise in Machine Learning, Neural Networks, Natural Language Processing, Computer Vision, and more, ensuring you stay ahead in the evolving AI landscape.

**Comprehensive AI Curriculum:** Covers machine learning, neural networks, NLP, and computer vision.

**Expert-Led Training:** Learn from experienced KPMG professionals.

**Hands-On Projects:** Solve real-world problems using Python and TensorFlow.

**Industry Certification:** Receive a KPMG-recognized AI certification.

**Tool Mastery:** Gain expertise in Python, TensorFlow, and SQL.

**Real-World Applications:** Apply AI techniques to solve practical industry challenges.

**Internship Opportunities:** Apply for a paid internship after you complete the program.

**Flexible Learning:** Learn anytime, anywhere with our expert-led recorded lectures.

\*Paid internship will be as per organization's norms or on a first-come, first-serve basis.

Hurry! First batch intake closes on 30 Aug 2026 — only 5 internship spots left!

## Skills you'll gain

###### Data Preprocessing

Techniques to clean and prepare datasets.

###### Feature Scaling and Transformation

Adjusting data for optimal model performance.

###### Regression Techniques

Applying linear and logistic regression for predictions.

###### TensorFlow

Mastering the leading AI framework for model building.

###### Neural Networks

Designing and training ANNs, CNNs, and RNNs.

###### Image Classification

Building CNN models for object and image recognition.

###### Natural Language Processing (NLP)

Analyzing and processing textual data.

###### Industry-relevant Skills

Real-world professional experience through an internship\*.

## Tools and Platforms covered

## 

1\. Introduction to Machine Learning

Learn essential data preparation techniques, including preprocessing, feature scaling, and categorical conversions. Master linear, multiple, ridge, lasso, and logistic regression models. Build a solid foundation in machine learning concepts to understand and implement basic predictive models effectively.

1.  Data Preprocessing
2.  Data Transformation
3.  Data Reduction
4.  Data Wrangling and Manipulation for Machine Learning
5.  Feature Scaling
6.  Categorical Conversions
7.  Introduction to Machine Learning
8.  Simple Linear Regression
9.  Machine Learning Basics
10.  Multiple Linear Regression
11.  Ridge and Lasso Regression
12.  Logistic Regression

## 

2\. Artificial Intelligence: Fundamentals

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3\. Artificial Neural Networks (ANN)             

## 

4\. Convolutional Neural Networks (CNN)

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5\. Sequential Data Analysis

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6\. Computer Vision and Video Analytics

## Earn and Share Your Certificate

## Meet our top-ranked faculty

###### Kaushik Swaroop

Consultant Advisory-Transformation-BE, KPMG India

## Amity Online Advantages: Why We're the Right Fit for You

Learn from Analytics Experts and Industry Veterans

Learn from experienced faculty and industry professionals who specialize in AI & ML. Our experts help you build dynamic skills and knowledge that meet industry standards.

Real-World Case Studies and Data-Driven Projects

Gain hands-on experience in Machine Learning, Neural Networks, NLP, and Computer Vision. This practical approach prepares you to make data-driven decisions in any business setting.

Flexible Learning for Busy Professionals

Study at your own pace with a flexible curriculum designed to fit around your schedule, making it ideal for working professionals looking to upskill.

Certification with Industry Recognition

Receive a certification in Artificial Intelligence and Deep learning using Python from Amity University Online, respected by employers across multiple sectors.

-   ##### Total Modules: 6
    
    Gain insight into a topic and learn the fundamentals.
    

-   ##### Duration
    
    40 hours
    

-   ##### Level: Beginner
    
    No prior experience required
    

-   ##### Internship
    
    Be eligible for internship (paid/unpaid)
    

-   ##### Fee: ₹~~52,000~~ ₹30,000


## Program Overview and Structure

### 1\. Introduction to Machine Learning

Learn essential data preparation techniques, including preprocessing, feature scaling, and categorical conversions. Master linear, multiple, ridge, lasso, and logistic regression models. Build a solid foundation in machine learning concepts to understand and implement basic predictive models effectively.

1.  Data Preprocessing
2.  Data Transformation
3.  Data Reduction
4.  Data Wrangling and Manipulation for Machine Learning
5.  Feature Scaling
6.  Categorical Conversions
7.  Introduction to Machine Learning
8.  Simple Linear Regression
9.  Machine Learning Basics
10.  Multiple Linear Regression
11.  Ridge and Lasso Regression
12.  Logistic Regression

### 2\. Artificial Intelligence: Fundamentals

Understand the basics of AI, TensorFlow, and neural networks. Learn TensorFlow calculations, automatic differentiation, and loss functions. Get hands-on experience with activation functions and neural network architecture to start designing AI models with confidence.

1.  Introduction to AI
2.  Introduction to TensorFlow
3.  Working of TensorFlow
4.  TensorFlow Calculations
5.  Automatic Differentiation
6.  Introduction to Neural Networks
7.  Introduction to Activation Functions
8.  Activation Functions
9.  Loss Functions

### 3\. Artificial Neural Networks (ANN)

Dive deep into artificial neural networks, gradient descent, and stochastic gradient descent. Learn to evaluate ANN models for classification and regression tasks using early stopping and perceptron models. Build the expertise to train and optimize neural networks for various applications.

1.  Artificial Neural Networks (ANN)
2.  Gradient Descent
3.  Stochastic Gradient Descent
4.  Evaluation Method – Classification
5.  Regression in ANN
6.  Classification in ANN
7.  Early Stopping
8.  Perceptron Models

### 4\. Convolutional Neural Networks (CNN)

Master the fundamentals of CNNs, including building and training CNN models. Learn image classification techniques and implement CNNs in Python. Develop the ability to apply CNNs for real-world image recognition tasks.

1.  Introduction to CNN
2.  Building CNN
3.  CNN Models
4.  Image Classification in CNN
5.  CNN Model Building in Python

### 5\. Sequential Data Analysis

Explore Natural Language Processing (NLP) and Natural Language Understanding (NLU). Learn text preprocessing, bag of words, TF-IDF, sentiment analysis, and POS tagging. Understand sequential data with RNNs and LSTMs and tackle vanishing gradient problems for advanced text analytics.

1.  Introduction to NLP and NLU
2.  Bag of Words and NLP Processing
3.  DTM (Document-Term Matrix)
4.  N-gram Analysis
5.  TF-IDF (Term Frequency-Inverse
6.  Document Frequency)
7.  Library Installation and NLP Text
8.  Preprocessing
9.  Sentiment Analysis
10.  POS Tagging
11.  Introduction to RNN and LSTM
12.  Vanishing Gradient Problem
13.  RNN Text Analytics
14.  LSTM (Long Short-Term Memory)

### 6\. Computer Vision and Video Analytics

Gain expertise in computer vision techniques, including image representation, edge detection, and thresholding. Learn face and object detection using Haar Cascade Classifier and SSD. Explore video analysis techniques in Python, enabling practical applications like real-time detection and tracking.

1.  Introduction to Computer Vision
2.  Image Representation
3.  Black and White Conversion
4.  Working of Computer Vision
5.  Edge Detection Filters
6.  Simple Thresholding and Adaptive
7.  Thresholding
8.  Face and Eye Detection using Haar
9.  Cascade Classifier
10.  Object Detection using SSD
11.  Video Analysis in Python


## Frequently Asked Questions

### What makes these certifications unique?

These certifications are unique because they combine expert-led instruction with hands-on projects, focusing on practical applications of AI and deep learning using Python, preparing you for real-world industry demands.

### Who is this program for?

This program is for professionals, students, and tech enthusiasts who want to build expertise in artificial intelligence and deep learning using Python to advance their careers in AI, machine learning, and data science fields.

### What are the prerequisites for enrollment?

The prerequisites for enrollment include a basic understanding of programming, familiarity with Python, and a foundational knowledge of mathematics and statistics.

### What tools and technologies will I learn?

You will learn tools and technologies like Python, TensorFlow, Keras, and other AI and deep learning libraries essential for building and deploying intelligent systems and models.

### How is the program structured?

The program is structured to provide a comprehensive understanding of artificial intelligence and deep learning using Python through interactive video lectures, hands-on projects, and real-world case studies to ensure practical skill development.

### Will I receive a certificate upon completion?

Yes, students will receive a certification upon successfully completing the program.

### How can I apply what I learn to my career?

You can apply what you learn by developing AI and deep learning models to solve complex problems, automate tasks, and drive innovation, helping you grow in careers like AI engineer, machine learning specialist, or data scientist.

### Does this program offer a paid internship?

Yes! Students who successfully complete the program may become eligible for a paid internship with KPMG or its associates, depending on selection criteria.

### What roles are available in the paid internship?

Interns work in consulting, analytics, product development, and business intelligence, handling dashboard development, data analysis, and strategic problem-solving.

### How much is the stipend?

The average internship stipend is ₹8,000 per month.

### Where are the paid internships conducted?

Paid internships are conducted in-person at KPMG India offices in cities such as: Gurugram, Noida, Bangalore, Mumbai, Pune, Chennai, Kochi, Kolkata, Chandigarh, and Ahmedabad.

### When do paid internships start?

Paid internships are offered quarterly, with the selection process taking place in the last week of each quarter.

### Can I reapply if I don’t get selected?

Yes, students can reapply twice, but only in alternate quarters. If a student declines a paid internship after selection, they will not be eligible to reapply.

### How do I enroll and what are the payment options?

You can enroll by visiting our website and following the enrollment instructions. We offer various payment options, including credit/debit cards, online banking, and installment plans.

### Can I access course materials after completion?

Yes, students will have continued access to learning materials even after completing the course.