Artificial Intelligence and Machine Learning Internships

Training is designed by industry professionals as per the industry requirements & demands.

Build a solid foundation by covering the most popular & widely used artificial intelligence technologies.




4.4 star (3)  star (3)  star (3) star (3) star (2) (2,230 ratings) 5,815 students

Learn from top college Lecturers in Bangalore


What you'll learn?

  • Fundamentals: Build a strong foundation in AI and machine learning.
  • Hands-On Projects: Gain practical experience through real-world projects.
  • Data Skills: Master data collection, cleaning, and preprocessing.
  • Machine Learning Algorithms: Exploring a variety of machine learning algorithms, including supervised and unsupervised learning, regression, and classification.



  • Deep Learning: Delving into deep neural networks, convolutional neural networks (CNNs), and recurrent neural networks (RNNs) for tasks like image and natural language processing
  • Model Deployment: Deploy models in real-world applications.
  • Tools and Frameworks: Work with industry-standard tools like TensorFlow and PyTorch for AI and ML development.


Curated Exclusively For Engineering Students


  • Engineering students from 1st year through the final year of branches ECE,CSE, EEE,ISE  
  • Knowledgeable with basic C programming, Python
  • Hands-on experience in various tools

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Summary : 

"We offer dynamic internships that empower you to delve into AI and machine learning. You'll apply these technologies to tackle real-world challenges, contribute to cutting-edge research, redefine industry standards, and create innovative theories that revolutionize our understanding of machine learning and its practical applications."


"Our AI and ML internship program is designed to provide you with exceptional technical mentorship, enabling you to embark on a continuous learning journey. You'll acquire practical skills, gain hands-on experience, deepen your industry knowledge, and establish valuable professional connections. You'll become a part of an outstanding team, comprising world-class software engineers and leading researchers in machine learning, all driven by a shared passion for pioneering AI advancements.

We cover a broad spectrum of machine learning domains, including but not limited to large language models, diffusion models, and reinforcement learning, while also exploring related areas like accessibility, privacy, and fairness. Collaborating closely with your team, you'll have the opportunity to design and implement innovative solutions for real-world machine learning challenges with a meaningful impact.

Upon successful completion of the internship, you'll receive a certificate in compliance with university guidelines, recognizing your valuable contribution to the field of AI and machine learning."


Detailed Curriculum: Modules

  • Deep Learning: A revolution in Artificial Intelligence
  • Limitations of Machine Learning
  • What is Deep Learning?
  • Advantage of Deep Learning over Machine learning
  • 3 Reasons to go for Deep Learning
  • Real-Life use cases of Deep Learning
  • Review of Machine Learning: Regression, Classification, Clustering, Reinforcement
    Learning, Underfitting and Overfitting, Optimization

  • How Deep Learning Works?
  • Activation Functions
  • Illustrate Perceptron
  • Training a Perceptron
  • Important Parameters of Perceptron
  • What is TensorFlow?
  • TensorFlow code-basics
  • Graph Visualization
  • Constants, Placeholders, Variables
  • Creating a Model
  • Step by Step - Use-Case Implementation

  • Understand limitations of a Single Perceptron
  • Understand Neural Networks in Detail
  • Illustrate Multi-Layer Perceptron
  • Backpropagation – Learning Algorithm
  • Understand Backpropagation – Using Neural Network Example
  • MLP Digit-Classifier using TensorFlow
  • TensorBoard

  • Why Deep Networks
  • Why Deep Networks give better accuracy?
  • Use-Case Implementation on SONAR dataset
  • Understand How Deep Network Works?
  • How Backpropagation Works?
  • Illustrate Forward pass, Backward pass
  • Different variants of Gradient Descent
  • Types of Deep Networks

  •  Introduction to CNNs
  • CNNs Application
  • Architecture of a CNN
  • Convolution and Pooling layers in a CNN
  • Understanding and Visualizing a CNN
  • Understanding and Visualizing a CNN

  •  Introduction to RNN Model
  • Application use cases of RNN
  • Modelling sequences
  • Training RNNs with Backpropagation
  • Long Short-Term memory (LSTM)
  • Recursive Neural Tensor Network Theory
  •  Recurrent Neural Network Model

Tools Covered

python (2)
scipy (1)


I completed my full stack developer internship from CITL vijaynagar For 1 month during which i have got good programing knowledge on python, django and web development. Good infrastructure with equipped lab facility skilled & well experienced trainers




I have completed my full python programing internship from CITL vijaynagar For 1 month during which i have got good programing knowledge on python, django and web development. Good infrastructure with equipped lab facility skilled & well experienced trainers


Bhuvan kumar R


I have completed my python machine learning internship from citl vijaynagar for month during which i have got good programming knowledge on a concepts, I worked on 2 projects hand-on. As we gave project presentation we have improved our presentation & also communications skills and fr. are very helpful and friendly. Good Infrastructure with equipped lab facility skilled & well experienced trainers





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