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Software Training Institute in Chennai with 100% Placements – SLA Institute

Deep Learning Online Training

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1.5 Months
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Our Deep Learning Online Training programs are designed for students, freshers, and working professionals who want to upskill and stay relevant. We offer Deep Learning Online Courses that are practical, interactive, and aligned with the latest industry demands. Our Deep Learning Syllabus covers the deep learning fundamentals, perceptrons, activation functions, convolutional neural networks (CNNs), recurrent neural networks (RNNs), natural language processing (NLP), and model deployment. Enroll now and learn from industry experts with flexible timings and get Job support.

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Ready to start your tech career? Whether you have recently graduated and want to begin your IT career, or want to upskill for your next phase, our Eligibility Assessment Form makes the process easy to begin. For this Deep Learning Online Course Developer Course, we will match your skills and goals to the best training structure for you. Just fill in the form below for an easy start on your course. Take your first step today!
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Syllabus of Deep Learning Online Course

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  • what is neural network..?
  • How neural networks works?
  • Gradient descent
  • Stochastic Gradient descent
  • Perceptron
  • Multilayer Perceptron
  • BackPropagation
  • Overview of deep learning
  • DL environment setup locally
    • Installing Tensorflow
    • Installing Keras
  • Setting up a DL environment in the cloud
    • AWS
    • GCP
  • Run Tensorflow program on AWS cloud plateform
  • Placeholders in Tensorflow
    • Defining placeholders
    • Feeding placeholders with data
  • Variables,
  • Constant
  • Computation graph
  • Visualize graph with Tensor Board
  • What are activation functions?
  • Sigmoid function
  • Hyperbolic Tangent function
  • ReLu -Rectified Linear units
  • Softmax function
  • Exploring the MNIST dataset
  • Defining the hyperparameters
  • Model definition
  • Building the training loop
  • Overfitting and Underfitting
  • Building Inference
  • Learning word vectors
    • Loading all dependencies
    • Preparing the text corpus
    • defining our word2vec model
    • Training the model
    • Analyzing the model
  • Visualizing the embedding space by plotting the model on tensorboard
  • Introduction to CNN
  • Train a simple convolutional neural net
  • Pooling layer in CNN
  • Building ,training and evaluating our first CNN
  • Model performance optimization
  • Introduction to Imagenet
  • LeNet architecture
  • AlexNet architecture
  • VGGNet architecture
  • ResNet architecture
  • What are Recurrent Neural Networks (RNNs)?
  • Understanding a Recurrent Neuron in Detail
  • Long Short-Term Memory(LSTM)
  • Back propagation Through Time(BPTT)
  • Implementation of RNN in Keras
  • Code Implementation
    • Importing all of the dependencies
    • Defining the hyperparameters
    • Building a simple deep neural network
    • Convolution in keras
    • Pooling
    • Dropout technique
    • Data augmentation

Objectives of Deep Learning Online Course

Our Deep Learning Online Training is your best choice to learn from our new and updated syllabus, which includes trending topics, that was curated by our experts in the IT industry, that makes this syllabus a reliable one to learn. Some of the topics in the syllabus are briefly discussed below:

  • The syllabus begins with fundamental topics like, What is neural network, Gradient Descent, Perceptron etc.
  • The syllabus then moves a little deeper into deep learning through topics like, TensorFlow Basics, Activation Functions, Word Representation using word2vec etc.
  • The syllabus then moves to advanced topics like, Popular CNN Model Architectures, Recurrent NEural Network etc.
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Highlights of Deep Learning Online Course?

Deep learning, a branch of machine learning, employs multi-layered artificial neural networks to discern patterns from vast datasets, mirroring the human brain’s processing mechanism. Through layers of interconnected neurons, deep learning algorithms can autonomously learn data features and complex hierarchies, facilitating tasks like image recognition, speech analysis, and decision-making. Its effectiveness spans across domains like computer vision, speech recognition, and healthcare, showcasing notable achievements.

The following are the reasons for learning Deep Learning:

  • Advanced Problem Solving: Deep learning gives you powerful tools to solve complicated problems in areas like recognizing images and speech, understanding natural language, and building autonomous systems.
  • Cutting-Edge Technology: Deep learning is a leading area of research in artificial intelligence, offering exciting opportunities to be part of a field that is constantly evolving.
  • Career Opportunities: Learning deep learning opens doors to many job options in industries such as technology, healthcare, finance, and more, where there’s a high demand for AI skills

SLA does not demand any prerequisites for any courses as all the courses cover topics from fundamental to advanced level. However having a basic knowledge on these below topics can be beneficial in learning Deep Learning easily:

  • Programming Skills: You need to be good at using programming languages like Python to create deep learning programs and work with popular libraries like TensorFlow and PyTorch.
  • Mathematics: It’s important to understand math subjects like algebra, calculus, and probability because they help you understand the math behind deep learning.
  • Machine Learning Basics: Knowing about machine learning concepts and types, such as supervised and unsupervised learning, as well as neural networks, gives you a good starting point for deep learning.

Our Deep Learning Course is suitable for: 

  • Students
  • Job Seekers
  • Freshers
  • IT professionals aiming to enhance their skills
  • Professionals seeking career change
  • Enthusiastic programmers

The fees for our Deep Learning Course in Chennai depend on the program level (basic, intermediate, or advanced) and the course format (online or in-person). On average, the Deep Learning Course Fees in Chennai comes around 25,000 INR for a duration of 1.5 Months, inclusive of international certification. For precise and up-to-date details on fees, duration, and certification, kindly contact our Best Deep Learning Training Institute in Chennai directly.

The following are some of the jobs related to Deep Learning:

  • Data Scientist
  • Machine Learning Engineer
  • Deep Learning Researcher
  • Computer Vision Engineer

The Data Scientist freshers salary typically with less than 2 years of experience earn approximately ₹8-9 lakhs annually. For a mid-career Data Scientist with around 4 years of experience, the average annual salary is around ₹14-15 lakhs. An experienced Data Scientist with more than 7 years of experience can anticipate an average yearly salary of around ₹19-20 lakhs. Visit SLA for more courses.

Here are several real time Deep Learning applications:

  • Real-Time Object Detection
  • Speech Recognition System
  • Anomaly Detection in IoT Data
  • Real time Gesture Recognition

Boost your skills with Deep Learning Online Course with Experts

Our Mentors are from Top Companies like:

The following are our trainer’s profile for the Deep Learning Online Training:

  • We Deep Learning Trainer with over 6 years of industrial experience specializing in deep learning.
  • They are skilled in delivering comprehensive lectures, workshops, and practical exercises to teach artificial intelligence principles.
  • They are proficient with popular deep learning frameworks like PyTorch, TensorFlow, and Keras, and well-acquainted with big data technologies such as Apache Spark, Cassandra, and Kafka.
  • They are capable of tailoring training modules to suit individual learner requirements.
  • They possess excellent interpersonal and communication skills, adept at simplifying complex concepts.
  • They are passionate about sharing knowledge on artificial intelligence and deep learning applications.
  • They are proficient in scripting and animating Deep Learning training materials for courses in Chennai.
  • Committed to ensuring students acquire in-depth understanding of artificial intelligence, Machine Learning, and Deep Learning.
  • Highly competent in assisting students in crafting customized resumes tailored to industrial standards.
  • Motivated to facilitate student placements by providing expert guidance and interview preparation support.
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Explore Real Projects Built by Softlogic Students

Explore the real-world, enterprise-level projects designed and executed by our successful alumni. Gain the same hands-on exposure to live industry projects, build a standout portfolio, and prove your practical skills to top hiring managers instantly.
Real-Time Quality Inspection in Manufacturing
Continuous Gesture-Based Control
Live Traffic Sign Recognition
Project Practices for Deep Learning Online Course

Why Softlogic Systems is the Best Choice for Deep Learning Online Course

Crowdfunding Platform
Online & Offline Training Options
Learn at your convenience with flexible classroom and live online training.
Learn from 100+ Real-Time Developers
Get trained by industry professionals with years of hands-on experience.
Voting System with Python Django
Hands-on Projects & Codeathons
Practice with real-time projects and coding challenges to build confidence.
0% EMI Fee Options
Pay your course fees flexibly with easy EMI plans at zero interest.
Resume & Interview Support
Get expert help with resume building, mock interviews, and soft skills.
Placement with Top IT Firms
Access placement opportunities with leading MNCs and IT companies.
500+ Hiring Partners
Benefit from Softlogic’s strong recruiter network for faster job placement.
No Backdoor Jobs
We ensure only genuine placement opportunities with trusted companies.
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Certifications

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Get a certifications through our training programs to gain a competitive edge in the industry.
Stand Out from the Crowd with Codethon Certificate
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The Global Edge: Certified Vs. Uncertified

With Global Certification

  • ✅ Visibility in ATS Filters
  • ✅Command Higher Hikes
  • ✅ Verified Skill Proof
  • ✅Global Job Access
  • ✅ Fast-Tracked Senior Roles

Without Global Certification

  • ❌ Stuck in Screening
  • ❌ Lower Starting Pay
  • ❌ Unproven Technical Ability
  • ❌ Limited Local Scope
  • ❌ Slower Career Leader
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The SLA Way to Get Placed

The SLA Way to Get Placed

Seven connected stages, one continuous path from enrollment to your career launch — here is exactly how it works, step by step.

01
🎓

Technical Mastery

Industry-aligned curriculum, daily coding tasks, real-time projects

02
💻

Career Readiness

Aptitude, Communication, ATS-friendly resume optimization

03
🎯

Placement Prep

Aptitude, communication tuning and technical interview mastery.

04
💬

Panel Mock Interviews

Real company-pattern mocks with expert panel feedback.

05
👨‍💼

Interview schedule

Multiple company drives with lifetime placement support.

06
📝

Interview Feedback

Detailed performance analysis and one-on-one guidance.

07
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Launch Your Career

Land your first job with lifetime alumni and career support.

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FAQ

Yes, SLA is completely equipped with resources like, SMART classroom, computers and related technologies, to conduct online classes. 

SLA supports EMI, with 0% interest.

SLA has two branches currently, one is in Navalur, OMR and another is in K.K. Nagar.

SLA’s OMR branch is located among OMR’s IT hub, which gives ample opportunity for students in internship and placement.

SLA’s payment methods includes cash, cheque, cards, EMIs and UPIs.

The vanishing gradient problem happens when gradients in deep neural networks become very small during training, causing slow convergence. Techniques like using different activation functions (e.g., ReLU), careful weight initialization, or methods like batch normalization can help mitigate this issue.

Transfer learning means using pre-trained models from one task to solve a related task with limited labeled data. It’s handy when you have a small dataset for your target task but a large one for a related task, letting you transfer knowledge and improve performance.

Regularization techniques such as L1 and L2 regularization, dropout, and early stopping are used to prevent overfitting in deep learning models. They introduce constraints on the model’s parameters or training process, reducing its capacity and preventing it from fitting noise in the training data, thus improving generalization performance.

Hyperparameters are parameters set before training, controlling aspects like learning rate, batch size, and network architecture. They significantly impact model performance, as choosing appropriate values can lead to faster convergence, better generalization, and improved overall performance.

Supervised learning learns from labeled input-output pairs, predicting outputs given new inputs. Unsupervised learning discovers patterns and structure from unlabeled data, while semi-supervised learning combines both labeled and unlabeled data to enhance performance, especially when labeled data is scarce.

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