Deep Learning with Python Training in Chennai

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Deep Learning with Python Course Overview

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Upcoming Deep Learning with Python Batches

21-09-2026
Mon-FriWeekdays Regular
08:00 AM & 10:00 AM Batches(Class 1Hr - 2Hrs) / Per Session
23-09-2026
Mon - FriWeekdays Regular
06:00 PM & 08:00 PM Batches(Class 1Hr - 2Hrs) / Per Session
18-09-2026
Sat-SunWeekend Batch
09:00 AM & 01:00 PM Batches(Class 2Hr - 4Hrs) / Per Session
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Deep Learning with Python Course Syllabus

Join our Deep Learning with Python Course and build practical expertise in developing intelligent applications using neural networks and modern deep learning techniques. Learn Python, NumPy, Pandas, TensorFlow, and Keras while exploring artificial neural networks, CNNs, RNNs, transfer learning, computer vision, and natural language processing. Through hands-on projects and industry-oriented training, gain the skills needed to design, train, evaluate, and deploy deep learning models for real-world applications.

  • Introduction to Artificial Intelligence, Machine Learning & Deep Learning
  • Deep Learning applications and use cases
  • Machine Learning vs Deep Learning
  • Deep Learning workflow
  • Types of neural networks
  • Deep Learning ecosystem and tools
  • Python fundamentals
  • Variables, data types, loops and functions
  • Object-oriented programming basics
  • NumPy for numerical computing
  • Pandas for data manipulation
  • Matplotlib for data visualization
  • Working with Jupyter Notebook
  • Linear algebra fundamentals
  • Vectors and matrices
  • Matrix operations
  • Probability concepts
  • Mean, variance and standard deviation
  • Derivatives and gradients
  • Introduction to optimization
  • Mathematical foundations of neural networks
  • Understanding datasets
  • Data collection and loading
  • Data cleaning
  • Handling missing values
  • Feature scaling and normalization
  • Encoding categorical variables
  • Train, validation and test datasets
  • Data augmentation fundamentals
  • Neural network architecture
  • Neurons and layers
  • Weights and biases
  • Activation functions
  • Forward propagation
  • Loss functions
  • Backpropagation
  • Gradient descent
  • Optimizers
  • Building ANN models with Python
  • Introduction to TensorFlow
  • Keras framework
  • Creating neural network models
  • Sequential and functional APIs
  • Model compilation
  • Training and validation
  • Callbacks
  • Saving and loading models
  • Model evaluation
  • Introduction to computer vision
  • CNN architecture
  • Convolution operation
  • Filters and feature maps
  • Pooling layers
  • Flattening and fully connected layers
  • Image classification
  • CNN model development using Python
  • Image preprocessing and augmentation
  • Transfer learning concepts
  • Pre-trained models
  • VGG, ResNet and MobileNet
  • Feature extraction
  • Fine-tuning
  • Image classification using pre-trained models
  • Practical computer vision applications
  • Introduction to sequential data
  • RNN architecture
  • Sequence processing
  • Vanishing and exploding gradients
  • LSTM networks
  • GRU networks
  • Time-series prediction
  • Text sequence analysis
  • Introduction to NLP
  • Text preprocessing
  • Tokenization
  • Word embeddings
  • Sentiment analysis
  • Text classification
  • Sequence models for NLP
  • Building NLP applications with Python
  • Training and validation strategies
  • Overfitting and underfitting
  • Regularization
  • Dropout
  • Batch normalization
  • Hyperparameter tuning
  • Performance metrics
  • Confusion matrix
  • Model optimization techniques
  • Introduction to Generative AI
  • Generative models
  • Autoencoders
  • Generative Adversarial Networks (GANs)
  • Introduction to Transformers
  • Large Language Models overview
  • Applications of Generative AI
  • Deep learning trends and industry applications
  • Saving and loading trained models
  • Model inference
  • Introduction to APIs
  • Deploying models using Flask/FastAPI
  • Creating simple AI applications
  • Cloud deployment concepts
  • Model monitoring and maintenance
  • Image Classification System
  • Customer Sentiment Analysis
  • Sales/Time-Series Forecasting
  • Dataset preparation and preprocessing
  • Model development and training
  • Performance evaluation
  • Model deployment
  • Project presentation and documentation
Need customized curriculum?
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Deep Learning with Python Hands on Projects

Gain practical experience through hands-on Deep Learning with Python Course projects designed around real-world applications. Learn to prepare datasets, build and train neural networks, evaluate model performance, and deploy intelligent solutions using Python, TensorFlow, and Keras. These projects strengthen your problem-solving skills and provide practical exposure to computer vision, NLP, and predictive analytics.

Image Classification Using CNN

Build an image classification system using Convolutional Neural Networks (CNNs) to automatically identify and categorize images. Perform image preprocessing, data augmentation, model training, validation, and performance evaluation using Python, TensorFlow, and Keras.

Customer Sentiment Analysis Using NLP

Develop a deep learning model to classify customer reviews as positive, negative, or neutral. Apply Natural Language Processing (NLP) techniques, text preprocessing, word embeddings, and LSTM networks to analyze customer feedback and generate meaningful sentiment insights.

Time-Series Sales Forecasting

Create a deep learning-based forecasting model to predict future sales using historical business data. Apply Python, Pandas, TensorFlow, and LSTM networks to preprocess time-series data, train the model, evaluate prediction accuracy, and generate forecasts to support business planning.

For Corporates

Educate your workforce with new skills to improve their performance and productivity.

Corporate Training
"Leading Companies We've Served"
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Our Instructor
Name
Mr. Vimal
Experience
8+ Years
Specialized in
Deep Learning, Python, TensorFlow, Keras, Machine Learning, Neural Networks, Computer Vision, Natural Language Processing (NLP), Generative AI & AI Model Development.
More Details
Mr. Vimal, with 8+ years of industry experience, specializes in Deep Learning, Python, TensorFlow, Keras, Machine Learning, Neural Networks, Computer Vision, NLP, and Generative AI. His practical, industry-focused approach helps learners understand complex AI concepts, develop real-world applications, and build strong technical skills through hands-on projects and guided implementation.

Deep Learning with Python Course Objectives

The Deep Learning with Python Course is designed to develop practical skills in building intelligent applications using neural networks and deep learning algorithms. Learners will master Python, TensorFlow, Keras, CNNs, RNNs, LSTMs, NLP, and model deployment while working on real-world projects to strengthen their problem-solving and AI development capabilities.

You will learn Python, TensorFlow, Keras, neural networks, CNNs, RNNs, LSTMs, NLP, computer vision, model optimization, and deployment techniques through practical training.

Yes. This course covers Python and deep learning concepts progressively, making it suitable for learners with basic programming knowledge who want to build expertise in AI and deep learning.

You will work on real-world projects such as image classification using CNN, customer sentiment analysis using NLP, and time-series sales forecasting using LSTM networks.

Job Assistance Program

Our Job Assistance Programme offers you special guidance through the course curriculum and helps in your interview preparation.

Specialised Curriculum
Get on-field knowledge and skills from our expert instructors.
Assessment
Upgrade your on-field skills with our assessments and track your progress in real time.
Hands-on Project
Our hands-on project help you gain experience in real-time working.
Certification Guidance
A global certificate always helps you stand out from the crowd.
Portfolio Building
Experts guide you to maximise your profile with current industry trends that employers expect.
Placment Cell
We promote your abilities and showcase your portfolio to employers.

Deep Learning with Python Course Career Opportunity

A Deep Learning with Python Course opens the door to exciting careers in the rapidly growing AI industry. Build expertise in neural networks, computer vision, NLP, and Generative AI to pursue roles such as Deep Learning Engineer, AI Engineer, Machine Learning Engineer, Computer Vision Engineer, NLP Engineer, and Python AI Developer. Gain practical project experience and industry-ready skills to confidently advance your career in artificial intelligence.

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Placement Guidance & Interview Preparation

Infibee’s placement guidance navigates you to your desired role in top organisations, ensuring you stand out and excel in every opportunity.

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I enrolled in the SAP ANALYTICS CLOUD course at Infibee Technologies and the classes were very well structured. The trainers possess industry experience and they delivered effective assistance with both resume creation and job placement services. This institution serves as the topmost educational center for SAP training courses.
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I recently completed the SAP CO-PA course at Infibee Technologies and had a great experience. The training quality was excellent, and the trainers were friendly, knowledgeable, and very supportive. They also provided valuable help with interview preparation and resume building, which boosted my confidence. With affordable fees and strong support, I highly recommend this institute for SAP training.
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I completed the Workday HR course at Infibee Technologies and the training was really helpful for my career growth. The trainers support students by providing simple explanations which include real-world examples of every topic. Highly recommended to join now.
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Deep Learning with Python Course FAQ's

Infibee Deep Learning with Python Course offers wide range of services that suits for both fresher and experienced persons via both offline and online at your suitable time slots.

You need not worry about having missed a class. Our dedicated course coordinator will help them with anything and everything related to administration. The coordinator will arrange a session for the student with trainers in place of the missed one.

Yes, of course. You can contact our team at Infibee Technologies, and we will schedule a free demo or a conference call with our mentor for you.

We provide classroom, online, and self-based study material and recorded sessions for students based on their individual preferences.

Yes, all our trainers are industry professionals with extensive experience in their respective domains. They bring hands-on practical and real-world knowledge to the training sessions.

Yes, participants typically receive access to course materials, including recorded sessions, assignments, and additional resources, even after the training concludes.

We provide placement assistance to students, including resume building, interview preparation, and job placement support for a wide range of software courses.

Yes, we offer customisation of the syllabus for both individual candidates and corporate also.

Yes, we offer corporate training solutions. Companies can contact us for customised programmes tailored to their team’s needs.

Participants need a stable internet connection and a device (computer, laptop, or tablet) with the necessary software installed. Detailed technical requirements are provided upon enrollment.

In most cases, such requests can be accommodated. Participants can reach out to our support team to discuss their preferences and explore available options.

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