GENERATIVE AI

Internship 2024

Embark on a journey through AI and deep learning with our course. From PyTorch basics to advanced GANs and VAEs, dive into projects like cancer prediction and image generation. Master essential tools and concepts for creating cutting-edge AI applications.

1/ 2 Months

Online

8+ Live Projects

Dual Certification

Ultimate Step towards your Career Goals​: Expert in AI Technologies

Get ahead with the FutureTech Industrial Internship Program: gain hands-on experience, connect with industry leaders, and develop cutting-edge skills. Earn a stipend, receive expert mentorship, and obtain a certificate to boost your career prospects. Transform your future with practical, real-world learning today

Internship Benifits

Mentorship

Receive guidance and insights from industry experts.

Hands-on Experience

Gain practical skills in a real-world cutting-edge projects.

Networking

Connect with professionals and peers in your field.

Skill Development

Enhance your technical and soft skills.

Career Advancement

Boost your resume with valuable experience.

Certificate

Get a certification to showcase your achievements.

AI Internship Overview

Dive deep into the exciting world of Generative AI and Deep Learning with our comprehensive course. This program covers fundamental and advanced concepts, from the basics of PyTorch to sophisticated applications using Generative Adversarial Networks (GANs) and Variational AutoEncoders (VAEs). You will gain practical experience through projects like breast cancer prediction, flight fare prediction, and image-to-image translation. Enhance your skills and knowledge to become proficient in these cutting-edge technologies.

Key Highlights:

Generative AI, Deep Learning, and PyTorch

  • Understand the core principles of generative AI and deep learning.

PyTorch Basics:

  • Tensor Creation: Learn how to create and manipulate tensors

Deep Learning Concepts:

  • Neural Networks: Basics of neural networks and their architecture.

Creating Basic Neural Network with PyTorch:

  • Step-by-step guide to designing and implementing a neural network using PyTorch.

Convolutional Neural Networks (CNN) in PyTorch:

  • Introduction to CNN: Understanding the structure and functions of CNNs.

Types of GANs and Applications: Explore different types of GANs and their use cases.

Variational AutoEncoders (VAE):

  • Basics and Applications: Understand VAEs and their use cases.

Generative AI, Deep Learning, and PyTorch Installation:

    • Understand the core principles of generative AI and deep learning.

    • Learn how to install PyTorch and set up your development environment.

PyTorch Basics:

    • Tensor Creation: Learn how to create and manipulate tensors.

    • Reshaping and Device Handling: Techniques for reshaping tensors and utilizing GPUs.

Deep Learning Concepts:

    • Neural Networks: Basics of neural networks and their architecture.

    • Activation Functions, Optimizers, Loss Functions: Key components in training neural networks

Creating Basic Neural Network with PyTorch:

  • Step-by-step guide to designing and implementing a neural network using PyTorch.

Practical Applications:

  • Breast Cancer Prediction Using ANN: Implementing an artificial neural network for predicting breast cancer.

  • Flight Fare Prediction Using ANN: Using the Wisconsin dataset to predict flight fares.

Introduction to Computer Vision:

    • Overview of computer vision concepts and applications.

    • Computer Vision Tools: Utilizing PyTorch and OpenCV for computer vision tasks.

Convolutional Neural Networks (CNN) in PyTorch:

    • Introduction to CNN: Understanding the structure and functions of CNNs.

    • Plant Disease Detection Using CNN: Applying CNN for detecting plant diseases.

  • Introduction to GANs:

    • Types of GANs and Applications: Explore different types of GANs and their use cases.

  • GAN Projects:

    • Handwritten Digits Generation Using PyTorch GAN: Create GANs to generate handwritten digits.

    • Realistic Face Generation with DCGAN on CelebA: Use Deep Convolutional GANs for face generation.

    • High-Quality Artwork Generation with Wasserstein GAN on CIFAR-10: Generate artwork using Wasserstein GAN.

    • Conditional Image Generation with CGAN on FashionMNIST: Implement Conditional GANs for image generation.

    • Image-to-Image Translation with Pix2Pix GAN on Cityscapes: Translate images from one domain to another.

    • Artistic Image Generation with Style GAN: Create artistic images using Style GAN.

    • Image Resolution Enhancement with SR-GAN on DIV2K: Enhance image resolution using Super-Resolution GAN.

    • Progressive High-Quality Faces with Pro-GAN on CelebA-HQ: Generate high-quality faces using Progressive GAN.

Introduction to Variational AutoEncoders (VAE):

  • Basics and Applications: Understand VAEs and their use cases.

  • Image Generation Using VAE: Implement VAEs for generating images.

Looking for in-depth Syllabus Information? Explore your endless possibilities in AI with our Brochure!

share this detailed brochure with your friends! Spread the word and help them discover the amazing opportunities awaiting them.

Project Submission: Example Output Screenshots from Our Clients

Take a look at these sample outputs crafted by our clients. These screenshots showcase the impressive results achieved through our courses and projects. Be inspired by their work and visualize what you can create!

Dual Certification: Internship Completion & Participation

Earn prestigious Dual Certification upon successful completion of our internship program. This recognition validates both your participation and the skills you have honed during the internship

iNTERNSHIP 2025

How does this Internship Program Work?

Step 1 Enroll in the Program

Choose Your Plan fit your needs

Master the Latest Industrial Skills. Select a technology domain & kick off your Internship immediately.

1 Month

₹1999/-

2 Month

₹3299/-

Our Learners Work at

Curious where our graduates make their mark? Our students go on to excel in leading tech companies, innovative startups, and prestigious research institutions. Their advanced skills and hands-on experience make them highly sought-after professionals in the industry.

FAQ

What kind of projects will I work on?

Projects range from basic tasks like building a recommendation system or salary prediction model to advanced projects like image classification, face recognition, and NLP applications.

Artificial Intelligence (AI) refers to the simulation of human intelligence in machines that are programmed to think, learn, and solve problems.

Python is a popular programming language known for its simplicity and readability, making it perfect for beginners and widely used in AI and machine learning.

Machine learning is a subset of AI focused on building algorithms that enable computers to learn from and make predictions based on data. Deep learning is a further subset that uses neural networks with many layers to analyze various factors of data.

Begin with understanding Python programming, then move on to learning key libraries like NumPy, Pandas, and Scikit-learn, followed by studying machine learning and deep learning concepts.

Utilize online tutorials, coding platforms like GitHub, and participate in competitions on sites like Kaggle to enhance your learning.

Start Your Tech Journey Today

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Training provided is in form of On-Campus Courses, In-House Courses, Faculty Development Programs, Hands on Sessions, Workshops and Seminars.

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