Advanced Deep Learning using Python

This 3 month program offers the student an advanced perspective to deep learning applications. Enroll in the program to kickstart your career in deep learning!

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

Course Overview

  • This course is designed based on the current industry trends and the needs of individuals who wish to learn deep learning algorithms.
  • This course involves advanced algorithms such as artificial, convolutional, and recurrent neural networks. 
  • Also, this course deals with the practical implementation of Tensorflow in python which is used by most of the organizations.

Course Syllabus

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

Week - 01 Artificial Neural Network (Feed Forward Neural Network)

  • In the introductory week, we will look into forward feed neural networks.
  • In this week's session, we will learn about:
    • Neural Network
    • Different architectures of Neural Networks
    • Importance of Neural Network
    • Hyperparameters in Neural Network
    • Different types of Gradient descent methods

Week - 02 Activation functions in neural networks

  • In the second week, we will look into activation functions.
  • In this week, we will learn about:
    • Conic sections
    • Hyperbolic trigonometric functions
    • Sigmoid activation function
    • Tanhx activation function
    • Relu activation function
    • Softmax activation function

Week - 03 Deep Learning

  • This week, we will be looking into-
    • Terminologies in deep learning
    • Nomenclature
    • Order of vectorized forms
    • Forward propagation derivation with 1 layer
    • Back propagation derivation with 1 layer
    • Batch size, iteration and epoch

Week - 04 Evaluation of models

  • In this week we will look into different topics related to the evaluation of models
    • Underfitting
    • Overfitting
    • Lasso regularization
    • Ridge regularization
    • Elastic Net regularization

Week - 05 Improvise the model

  • In this week, we will learn about:
    • Ensemble methods are meta-algorithms that combine several machine learning techniques into one predictive model in order to decrease variance, bias, or improve predictions.
    • Sparse and convex functions
    • Bagging to avoid overfitting
    • Boosting to avoid underfitting
    • Stacking to avoid underfitting

Week - 06 Optimizers

  • In this week we will look into the different types of regularisers and optimizers
    • Frobenius norm regularization
    • Data augmentation
    • Early stopping
    • Adam optimizer
    • Tensorflow 2.0


Week - 07 Convolutional Neural Network (CNN)-1

  • In deep learning, a convolutional neural network is a class of deep neural networks, most commonly applied to analyzing visual imagery.
  • In this week we will look at topics related to CNN such as:
    • Basics of CNN
    • Edge detection
    • Padding
    • Stride
    • Simple CNN
    • Difference between CNN & ANN


Week - 08 Convolutional Neural Network (CNN)-2

  • Here we will look at topics related to CNN, such as:
    • Pooling layers
    • Transfer learning
    • Examples of CNN architecture
    • Combination of different Neural network architecture
    • CNN in python


Week - 09 Recurrent Neural Network (RNN)-1

  • In this week's session, we will learn about:
    • RNN Model
    • Different types of RNN
    • Gradients in RNN
    • Back propagation
    • Difference between RNN & ANN


Week - 10 Recurrent Neural Network (RNN)-2

  • In this week, we will look at topics related to RNN:
    • Gated Recurrent Unit (RNN)
    • Long short term memory (LSTM)
    • Bidirectional RNN
    • RNN Implementation in Python



Week - 11 Basics of Natural Language Processing (NLP)

  • In this week's session, we will learn about:
    • Stop words
    • Stemming
    • Lemmatization
    • Word2vec
    • Implementation of word2vec in python



Week - 12 End-to-End ML Project steps

  • In this week's session, we will be performing an end-to-end ML/DL project for machine failure.
    • 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

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, the students are expected to work on - Logistic Regression -Gradient Descent


In this project, the students will be working on prediction of machine failure for the 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

Advanced Deep Learning using Python

The Advanced Deep Learning Certification program is a 3-month course that endeavours to present students with advanced-level viewpoints on deep learning employment and build a career in deep learning. This online course comprises comprehensive modules taught by proficient subject mentors. The total fees that students pay for this best deep learning course range from INR 7000 for 2 months to INR 15,000 for lifetime access. 

Deep learning courses help students understand the adoption of Artificial Intelligence to allow machines to acquire a task from practice without programming them, particularly about that task. (In simpler terms, machines read automatically without human help.)

Students understand how this method begins with feeding them high-grade data and then preparing the machines by creating various deep learning patterns using the data and complex algorithms. Moreover, learners read about the multiple algorithms that rely on people's data and automating tasks.

It is why there is a race amongst modern businesses to adopt deep learning. In addition, companies willingly spend large sums of funds in this deep learning adoption which includes hiring specialists because they understand what's at stake here and how this investment can yield tremendous returns. Also, students, after learning this course, make seamless transformations and warrant more result-oriented industry decision-making going into the future.

Who Should Take Up Advanced Deep Learning Course?

Deep learning is the ammunition that powers computers and bots. Machine learning provides companies with the expertise to develop programs that can transform and modernise machines and make them seamlessly accommodate various circumstances – for getting things done correctly and quickly. 

Therefore if you are an engineering or non-engineering graduate looking for a striking career opportunity in the machine learning field, this course is perfect for you. Moreover, the demand for skilled and proficient experts in Machine Learning is at its peak now, and in the coming future, it will only increase higher. 

In addition, the transcendent thing about a Deep learning career is that apart from job security and satisfaction, it also ensures substantial annual income and accelerated career growth. Hence we can say that it is the best time to enrol yourself for an advanced deep learning course at Skill Lync.

What Will You Learn?

There has remained a symbolic explosion in the practice of machine and deep learning in the present times. Students witness smart learning algorithms everywhere – from online marketing campaigns and mobile applications to emails and many more. It symbolises that a career in machine and deep learning is, at the moment, one of the most in-demand career options across the globe. 

Therefore if working with intelligent machines interests students, they must undoubtedly enrol on a deep learning online course

The Deep Learning Certification program establishes industry-driven projects that help students enhance their abilities and understanding of deep learning, Python programming language, and machine learning. Moreover, after completing this online course and accomplishing projects and examinations, students will get a final certificate. Also, learners will obtain insights into the following points:

  • Importance of Neural Network.
  • Forward feed neural networks.
  • Different types of Gradient descent methods.
  • Activation functions and hyperbolic trigonometric functions.
  • Sigmoid, Tanhx, Relu, and Softmax activation function.
  • Terminologies and Nomenclature in deep learning.
  • Steps in the evaluation of models.
  • Types of regularisers and optimisers.
  • Basics of CNN and RNN Model.
  • Basics Of NLP.
  • End-to-end Ml Project Steps. 

 Skills You Will Gain

  • Students get hands-on knowledge of Python along with deep learning techniques.
  • Students get jobs in high-profile corporations like Lam Research, Mercedes Benz, Nissan, Hyundai, and other influential companies that use deep learning and artificial intelligence.
  • The course can be chosen by students who wish to research further on high-level deep learning with Python.

Key Highlights of The Programme

  • After completing this online course, students can receive a merit certificate with a one-one and group zoom support sessions. 
  • The duration of this online course is around three months with flexible course fees.
  • After enrolling on this online course, students can get professional guidance from expert instructors and personalised support from expert engineers.

Career Opportunities after taking the course

After pursuing deep learning online courses, students can make a bright career in the following fields. 

  • Machine Learning Engineer: A Machine Learning Engineer is an expert that operates multiple deep learning practices using programming languages such as Java, Python, Scala, etc., with the relevant deep learning libraries. Some of the important skills needed for this are Probability, Programming, Statistics, Machine Learning Algorithms, Data Modeling, System Design, etc.
  • Data Scientist: A Data Scientist employs high-level analytics technologies, including Deep learning and predictive modelling, to manage, examine and understand large volumes of data and generate actionable penetrations. These are then applied to make marketing choices by the company officials.
  • Human-Centred Machine Learning Designer: Human-Centred Deep Learning links to Machine Learning algorithms that remain focused on humans. This indicates that a Human-Centered Machine Learning Designer creates different operations that can make human-centred Machine Learning based on data processing and model recognition. 

FAQs on Advanced Deep Learning using Python

1, What software skills do this certification course include?

This certification course will include the fundamentals of Python and machine learning algorithms in Python.

2, Will the students get a certificate after this Deep Learning Course completion?

No, students will get a final certificate of achievement after doing the course.

3, What is the duration of this Advanced deep learning course?

The duration of this certification course is around three months. 

4, What are the fees students need to pay for this online course?

The total fee for this course ranges from INR 7000 for 2 months to INR 15,000 for lifetime access. 

5, Will this course help me get a job?

Yes, this course will help earn a handsome job. 

6, Which companies use deep learning technology?

Companies like Lam Research, Mercedes Benz, Renault & Nissan, Hyundai, and Rolls Royce use this technology. 

7, Who can opt for this course?

Any person who is willing to know this industry better.

8, Why did deep learning become such a popular skill in such a brief period? 

The reason deep learning has become such a popular skill in such a brief period is that companies in the country and across the world are combining deep learning and artificial intelligence into their extant systems to make them intelligent and more productive.

Instructors profiles

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


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


8 years in the experience range

Instructors with 8 years extensive industry experience.


Areas of expertise

  • Machine Learning
  • Deep Learning

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