Tensorflows
With Techpratham, you can learn how to use TensorFlow to build, train, and deploy deep learning models for real-world use. Use Google's open-source framework to learn about AI and neural networks by doing.
Level
Advanced
Duration
8 weeks
Placement Client
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About Tensorflows
Techpratham's TensorFlow training gives you a full understanding of deep learning and machine learning with TensorFlow. Students will learn about neural networks, training models, transfer learning, and putting them on cloud and edge devices. Computer vision, natural language processing, and recommendation systems are some of the real-world uses that the course covers. By the end, you'll know how to use TensorFlow to make and deploy AI solutions that can grow.
Training Plan
About trainer
Working professional who is carrying more then 10 years of industry experience.
Decks & Updated Content
Access to updated presentation decks shared during live training sessions.
e-Book
E-book provided by TechPratham. All rights reserved.
Assignments & MCQs
Module-wise assignments and MCQs provided for practice.
Video Recording
Daily Session would be recorded and shared to the candidate.
Projects
Live projects will be provided for hands-on practice.
Resume Building
Expert-guided resume building with industry-focused content support.
Interview Preparation
Comprehensive interview preparation with real-time scenario practice.
Tensorflows
Course Curriculum
Introduction to TensorFlow
Learn the basics of TensorFlow and its ecosystem.
TensorFlow Environment Setup
Set up TensorFlow on local and cloud environments, including installation, configurations, and IDE integration.
TensorFlow Core Concepts
Understand TensorFlow’s architecture, computation graphs, tensors, and operations essential for model building.
Data Handling with TensorFlow
Learn how to preprocess, load, and manage datasets efficiently using TensorFlow Data APIs.
Building Neural Networks with Keras
Use TensorFlow’s high-level API (Keras) to build, train, and evaluate deep learning models easily.
Convolutional Neural Networks (CNNs)
Develop image classification and recognition models using TensorFlow and Keras CNN architectures.
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Who Should Take Tensorflows
IT Professionals
Non-IT Career Switchers
Fresh Graduates
Working Professionals
Ops/Administrators/HR
Developers
BA/QA Engineers
Cloud / Infra
IT Professionals
Non-IT Career Switchers
Fresh Graduates
Key Projects
<h1><strong>Tensorflows</strong></h1>
Image Classification with CNNs
Train and build a convolutional neural network to sort images from datasets like MNIST or CIFAR-10. Add more data and test performance on data that hasn't been seen before. Use TensorFlow Serving to put the model into use.
Text Sentiment Analysis with RNNs/LSTMs
Make a deep learning model that can tell the difference between good and bad text reviews. Use LSTMs and embeddings to model sequences, and then make the model available as an API for real-time predictions.
Recommendation System using TensorFlow
Use TensorFlow to make a recommendation engine that uses collaborative filtering. Train the model on data about how users interact with items, and then put it on a web interface so that it can give personalized recommendations.
Placement Process
Live Class with Industry Use Cases
- Interactive learning
- Real-world examples
- Expert guidance
- Doubt resolution
Daily Assignment & Weekly Assessments
- Hands-on practice
- Concept reinforcement
- Weekly evaluation
- Timely feedback
Project Testing & Deployment
- Project development
- Testing practice
- Deployment exposure
- Portfolio creation
Interview Preparation (Mock, PD, Alumni Session)
- Mock interviews
- Personal development
- Alumni guidance
- Confidence building
Resume Building
- Resume crafting
- Industry-focused format
- Skills highlighting
- Professional presentation
Placement
- Job assistance
- Interview support
- Career guidance
- Opportunity access
Knowledge Center
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Course FAQs
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