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Advanced Deep Learning using Python in Delhi

Gain an in-depth understanding about deep learning algorithms and their development using Python.

12 weeks long course | 100% Online

Learn from leading experts in the industry

Project based learning with 2 industry level projects that learners can showcase on LinkedIn.

Learn Key Tools & Technologies Python

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Syllabus

This course is full of best-in-class content by leading faculty and industry experts in the form of videos and projects

Course Overview

Automating machines to process information and replicate knowledge-levels like humans is the primary focus of deep learning and neural networks. Deep learning simplifies the process of gathering, assessing, and interpreting data sets for engineers, and offers a proactive solution to foreseeing events by studying patterns. Engineers can develop and study versatile deep learning codes using Python - making it a fundamental skill in the job industry. 

This course is focused on enriching engineers with theoretical and practical knowledge on the following: 

  • Feed forward neural networks
  • Activation functions
  • Deep learning algorithms
  • Convolutional neural networks
  • Recurrent neural networks
  • Natural language processing

You will also get to complete projects requiring extensive hands-on work with Python according to modern trends in the industry.

Course Syllabus in Delhi

On a daily basis we talk to companies in the likes of Tata Elxsi and Mahindra to fine tune our curriculum.

Week 1 - Artificial Neural Network (Feed Forward Neural Network)

This week will cover

  • Neural networks 
  • Different architectures of Neural Networks
  • Importance of Neural Networks
  • Hyperparameters in Neural Networks
  • Different types of Gradient descent methods

Week 2 - Activation Functions in Neural Networks

This week will cover

  • Conic sections
  • Hyperbolic trigonometric functions
  • Sigmoid activation function
  • Tanhx activation function
  • Relu activation function
  • Softmax activation function

Week 3 - Deep Learning

This week will cover

  • Deep learning terminologies
  • Nomenclature
  • Order of vectorized forms
  • Forward propagation derivation with 1 layer
  • Back propagation derivation with 1 layer
  • Batch size, iteration and epoch

Week 4 - Evaluation of Models

This week will cover

  • Underfitting
  • Overfitting
  • Lasso regularization
  • Ridge regularization
  • Elastic Net regularization

Week 5 - Improvising the Model

This week will cover

  • Ensemble methods
  • Sparse and convex functions
  • Bagging to avoid overfitting
  • Boosting to avoid underfitting
  • Stacking to avoid underfitting

Week 6 - Optimizers

This week will cover

  • Frobenius norm regularization
  • Data augmentation
  • Early stopping
  • Adam optimizer
  • Tensorflow 2.0

Week 7 - Convolutional Neural Network (CNN) - Part 1

This week will cover

  • Basics of CNN
  • Edge detection
  • Padding
  • Stride
  • Simple CNN
  • Difference between CNN & ANN

Week 8 - Convolutional Neural Network (CNN)- Part 2

This week will cover

  • Pooling layers
  • Transfer learning
  • Examples of CNN architecture
  • Combination of different Neural network architecture
  • CNN in Python

Week 9 - Recurrent Neural Network (RNN) - Part 1

This week will cover

  • RNN Model
  • Different types of RNN
  • Gradients in RNN
  • Back propagation
  • Difference between RNN & ANN

Week 10 - Recurrent Neural Network (RNN) - Part 2

This week will cover

  • Gated Recurrent Unit (RNN)
  • Long short term memory (LSTM)
  • Bidirectional RNN
  • RNN Implementation in Python

Week 11 - Basics of Natural Language Processing (NLP)

This week will cover

  • Stop words
  • Stemming
  • Lemmatization
  • Word2vec
  • Implementation of word2vec in Python

Week 12 - End-to-End ML Project Steps

This week will cover

  • Descriptive Analytics
  • Diagnostic Analytics
  • Predictive Analytics
  • Prescriptive Analytics

Our courses have been designed by industry experts to help students achieve their dream careers

Industry Projects in Delhi

Our projects are designed by experts in the industry to reflect industry standards. By working through our projects, Learners will gain a practical understanding of what they will take on at a larger-scale in the industry. In total, there are 2 Projects that are available in this program.

Logistic Regression and Gradient Descent

In this project, you will perform logistic regression and gradient descent on a given dataset using Python. 

ANN, CNN and RNN

In this project, you will have to work on prediction of machine failure for a given dataset using ANN (Hyperparameters is completely dependent on individuals to come up with the best model).

Our courses have been designed by industry experts to help students achieve their dream careers

Ratings & Reviews by Learners

Skill-Lync has received honest feedback from our learners around the globe.

Google Rating
4.6

Become an Expert With the Advanced Deep Learning using Python Course in Delhi By Skill-Lync

Deep learning is a branch of science that trains machines to make intelligent decisions, learn, and provide the expected output. Skill-Lync could be the best institute for machine learning in India that offers Advanced Deep Learning Courses to get a deeper understanding of the field. This is a 12-week comprehensive program that covers neural networks, deep learning, evaluation of models, optimizers, and more. 

This course is one of the best Deep Learning courses designed by experienced industry experts and covers the latest innovations in the field. The course gives importance to experience and aims to answer questions like what is deep learning AI with three projects designed to teach you all that you need to know about the field and the application of concepts learned. You can add the work of this artificial intelligence course in Delhi to your resume and LinkedIn profile to attract jobs in the field.

FAQs 

Why is the Advanced Deep Learning Course apt for you in Delhi?

Deep learning is becoming the primary technology to solve problems with similar learning patterns to give the right output. This is especially true in Computer Vision, another key technology that is now widely used for many use cases. This deep learning training in Delhi sets aspiring engineers on a path to success.

What are the prerequisites for opting for the Advanced Deep Learning Course in Delhi?

The course does not have a specific prerequisite. However, this course is ideal for computer science students, graduates, and professionals and anyone with interest in the field can opt.

What is the program fee for the Advanced Deep Learning Course in Delhi?

The machine learning course fee in Delhi is flexible and is available in three plans. The three payment plans consist of the basic, the pro, and the premium plan. The course fees under the basic plan are INR 7,000 per month for three months with two months of access, the pro plan is at INR 10,000 per month for three months with three months of access, and the premium plan is INR 15,000 per month for three months with a lifetime of access.

What are the benefits of the Advanced Deep Learning Course in Delhi by Skill-Lync?

Pursuing a Deep Learning Course at Skill-Lync would offer many benefits to you,

  • Industry-oriented curriculum.
  • Hands-on experience in solving industry projects.
  • Email and forum support from the technical support team to clear your doubts.
  • A certificate of completion.

What kind of career opportunities open up after completing the Advanced Deep Learning using Python course?

The advanced Deep Learning online course in Delhi will open many doors for you to join leading tech companies. Some roles you can apply for after completing the course are – 

  • Data Engineer
  • Research Analyst
  • Machine Learning Engineer
  • Natural Language Process Engineer

How much does a graduate with the Advanced Deep Learning Course certificate earn?

Engineering professionals in India with a deep learning certification earn between 5 to 17 lakh rupees per annum, with the average being close to 8 lakhs.

Instructors profiles

Our courses are designed by leading academicians and experienced industry professionals.

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1 industry expert

Our instructors are industry experts along with a passion to teach.

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8 years in the experience range

Instructors with 8 years extensive industry experience.

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Areas of expertise

  • Machine Learning
  • Deep Learning

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