TensorFlow is Google’s open-source machine learning and deep learning framework used to build, train, deploy, and scale artificial intelligence (AI) models. It is widely adopted for applications such as computer vision, natural language processing (NLP), recommendation systems, predictive analytics, time series forecasting, speech recognition, and generative AI. TensorFlow supports end-to-end machine learning workflows, from data preprocessing and model development to deployment on cloud, mobile, edge devices, and production environments.

This instructor-led online training provides comprehensive hands-on experience covering TensorFlow fundamentals, deep learning, neural networks, Keras, computer vision, NLP, transformers, TensorFlow Extended (TFX), TensorFlow Lite, TensorFlow Serving, MLOps, and real-world enterprise AI projects.

• Basic Python Programming
• Basic Mathematics (Linear Algebra, Probability, and Statistics)
• Basic Machine Learning Concepts (Recommended)
• NumPy and Pandas Fundamentals
• No prior TensorFlow experience required

Our TensorFlow Online Training is designed to help aspiring AI engineers, machine learning professionals, data scientists, and software developers master one of the world’s leading deep learning frameworks. Through expert-led sessions, hands-on projects, and real-world applications, you’ll gain the practical skills needed to build intelligent AI solutions.

Expert Trainers

Learn from experienced AI and Machine Learning professionals with extensive industry expertise in TensorFlow and deep learning technologies.

Comprehensive Course Curriculum

Master TensorFlow fundamentals, Neural Networks, Deep Learning, Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), Natural Language Processing (NLP), Computer Vision, TensorFlow Keras, Model Deployment, TensorBoard, and TensorFlow Lite.

Hands-On Practical Training

Build real-world AI and machine learning models through practical assignments, coding exercises, and industry-based projects.

Live Interactive Online Classes

Attend instructor-led live sessions with coding demonstrations, doubt-clearing sessions, and personalized mentoring.

Real-Time Projects

Gain practical experience by working on AI applications such as image classification, sentiment analysis, recommendation systems, object detection, and predictive analytics.

Flexible Learning Schedule

Choose weekday or weekend batches that fit your personal and professional commitments.

Lifetime Access to Recordings

Review class recordings, source code, datasets, presentations, and learning resources anytime for continuous learning.

Resume & Interview Preparation

Receive expert guidance on resume building, portfolio development, mock interviews, and TensorFlow interview questions.

Placement Assistance

Benefit from career guidance, job referrals, interview support, and placement assistance to help you secure AI and Machine Learning roles.

Lifetime Technical Support

Continue receiving technical assistance, project guidance, and access to updated course materials even after completing the training.

Affordable & Career-Oriented Training

Our cost-effective training equips you with practical, job-ready AI skills that are in high demand across industries.

Build Your AI Career with TensorFlow

Whether you’re a beginner, software developer, data analyst, machine learning engineer, or AI enthusiast, our TensorFlow Online Training provides the technical knowledge, hands-on experience, and career support needed to become a successful TensorFlow Developer, Machine Learning Engineer, or AI Professional.

Module 1: Introduction to Artificial Intelligence & TensorFlow

• Artificial Intelligence Fundamentals
• Machine Learning vs Deep Learning
• TensorFlow Overview
• TensorFlow Architecture
• TensorFlow Ecosystem
• TensorFlow Versions
• AI Applications
• Industry Use Cases

Module 2: Python for TensorFlow

• Python Refresher
• NumPy
• Pandas
• Matplotlib
• Data Manipulation
• Data Visualization
• Feature Engineering

Module 3: TensorFlow Fundamentals

• Installation
• TensorFlow Environment Setup
• Tensors
• Variables
• Constants
• Tensor Operations
• Graph Execution
• Eager Execution
• Automatic Differentiation

Module 4: TensorFlow Keras API

• Sequential API
• Functional API
• Model Subclassing
• Layers
• Activation Functions
• Loss Functions
• Optimizers
• Metrics
• Callbacks

Module 5: Artificial Neural Networks (ANN)

• Perceptrons
• Feedforward Networks
• Hidden Layers
• Backpropagation
• Gradient Descent
• Weight Initialization
• Model Training
• Hyperparameter Tuning

Module 6: Data Preprocessing

• Data Cleaning
• Missing Values
• Data Scaling
• Feature Encoding
• Feature Selection
• Dataset Splitting
• TensorFlow Data Pipelines
• TFRecord Files

Module 7: Model Training & Evaluation

• Model Compilation
• Training
• Validation
• Cross Validation
• Performance Metrics
• Confusion Matrix
• Precision
• Recall
• ROC-AUC
• Model Comparison

Module 8: Regularization Techniques

• Dropout
• Batch Normalization
• Early Stopping
• Learning Rate Scheduling
• Weight Regularization
• Callback Functions

Module 9: Convolutional Neural Networks (CNN)

• CNN Fundamentals
• Image Classification
• Convolution Layers
• Pooling Layers
• Feature Maps
• Image Augmentation
• Object Detection Overview
• Image Segmentation Basics

Module 10: Transfer Learning

• Pretrained Models
• MobileNet
• ResNet
• Inception
• EfficientNet
• Fine-Tuning
• Feature Extraction

Module 11: Computer Vision Projects

• Face Recognition
• Medical Image Classification
• Defect Detection
• OCR Introduction
• Image Classification
• Traffic Sign Recognition

Module 12: Recurrent Neural Networks (RNN)

• Sequence Data
• RNN Architecture
• Time Series Forecasting
• Sequence Prediction
• Language Modeling

Module 13: Long Short-Term Memory (LSTM)

• LSTM Architecture
• Time Series Analysis
• Stock Price Prediction
• Weather Forecasting
• Sentiment Analysis
• Sequence Modeling

Module 14: Gated Recurrent Units (GRU)

• GRU Concepts
• Sequence Learning
• Performance Optimization
• NLP Applications

Module 15: Natural Language Processing (NLP)

• Text Processing
• Tokenization
• Word Embeddings
• Text Vectorization
• Text Classification
• Sentiment Analysis
• Named Entity Recognition (NER)
• Text Summarization Overview

Module 16: Transformers

• Attention Mechanism
• Transformer Architecture
• Encoder & Decoder
• BERT Overview
• GPT Overview
• Hugging Face Integration
• Fine-Tuning Transformer Models

Module 17: TensorFlow Extended (TFX)

• TFX Overview
• Data Validation
• Data Transformation
• Model Training Pipelines
• Model Validation
• Pipeline Deployment

Module 18: TensorFlow Lite

• Mobile AI
• Edge AI
• Model Optimization
• Quantization
• Android Deployment
• IoT Applications

Module 19: TensorFlow Serving

• Model Export
• SavedModel Format
• REST APIs
• Docker Deployment
• Version Management
• Production Inference

Module 20: TensorFlow Hub

• Pretrained Models
• Feature Extraction
• Image Models
• NLP Models
• Reusable Components

Module 21: TensorBoard

• Experiment Tracking
• Graph Visualization
• Performance Monitoring
• Profiling
• Debugging

Module 22: Distributed Training

• Multi-GPU Training
• TPU Overview
• Distributed Strategies
• Mixed Precision Training
• Performance Optimization

Module 23: MLOps Fundamentals

• Model Versioning
• Experiment Tracking
• CI/CD Pipelines
• Monitoring
• Retraining Strategies
• Model Governance

Module 24: Explainable AI (XAI)

• Model Interpretability
• SHAP Overview
• LIME Overview
• Feature Importance
• Bias Detection
• Fairness Concepts

Module 25: Cloud Deployment

• Google Cloud Vertex AI Overview
• AWS SageMaker Overview
• Microsoft Azure Machine Learning Overview
• Cloud Storage
• Cloud Model Deployment
• Serverless Inference

Module 26: Real-Time Enterprise AI Projects

Participants will build multiple AI solutions, including:

• Customer Churn Prediction
• Fraud Detection
• Loan Approval Prediction
• Image Classification
• Face Mask Detection
• Medical Diagnosis Assistance
• Sales Forecasting
• Product Recommendation Engine
• Spam Email Detection
• Predictive Maintenance

Module 27: Industry Use Cases

• Healthcare
• Banking & Finance
• Manufacturing
• Retail & E-commerce
• Telecommunications
• Automotive
• Insurance
• Agriculture
• Cybersecurity
• Education

Module 28: TensorFlow Certification Preparation

Certification Topics

• TensorFlow Fundamentals
• Keras API
• CNN
• RNN
• LSTM
• Transformers
• TensorFlow Lite
• TensorFlow Serving
• TFX
• Deployment

Module 29: Interview Preparation

• TensorFlow Interview Questions
• Python Coding Exercises
• Deep Learning Scenarios
• CNN & Computer Vision Questions
• NLP Scenarios
• MLOps Questions
• TensorFlow Debugging
• Resume Preparation
• Mock Interviews

Module 30: Resume & Placement Assistance

• Resume Building
• LinkedIn Profile Optimization
• GitHub Portfolio Development
• AI Project Documentation
• Career Guidance
• Mock Interviews
• Placement Assistance