Hone Your Skills with Our Comprehensive Deep Learning Master Course

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Mastering in Deep Learning Course Overview

The Mastering in Deep Learning certification is a validation of expertise in advanced machine learning strategies, specifically deep learning. This certification involves the understanding and application of neural networks, algorithms, and data representation using tools and libraries like TensorFlow and Keras. It reflects a person's ability to solve complex business problems by harnessing the power of vast data and transforming them into actionable insights. Industries use this proficiency to drive strategic decisions, optimize operations, and create innovative solutions. The process of obtaining this skill set forms a vital part of an individual's journey to become a Deep Learning Engineer or Data Scientist.


The 1-on-1 Advantage

Get 1-on-1 session with our expert trainers at a date & time of your convenience.

Flexible Dates

Start your session at a date of your choice-weekend & evening slots included, and reschedule if necessary.

4-Hour Sessions

Training never been so convenient- attend training sessions 4-hour long for easy learning.

Destination Training

Attend trainings at some of the most loved cities such as Dubai, London, Delhi(India), Goa, Singapore, New York and Sydney.

You will learn:

Module 1: Machine Learning Fundamentals
  • Machine Basics basics
  • Linear algebra and Probability
  • ML Supervised Algorithms
  • ML Supervised Algorithms
  • Introducing Google Colab
  • Tensorflow basic syntax
  • Tensorflow Graphs
  • Tensorboard
  • Introduction to Deep Learning
  • What are the Limitations of Machine Learning
  • Advantage of Deep Learning over Machine learning
  • Reasons to go for Deep Learning
  • Real-Life use cases of Deep Learning
  • What is Deep Learning Networks
  • Why Deep Learning Networks
  • How Deep Learning Works
  • Feature Extraction
  • Working of Deep Network
  • Training using Backpropagation
  • Variants of Gradient Descent
  • Types of Deep Networks
  • Feed forward neural networks (FNN)
  • Convolutional neural networks (CNN)
  • Recurrent Neural networks (RNN)
  • Generative Adversarial Neural Networks (GAN)
  • Restricted Boltzmann Machine (RBM)
  • Introduction to Perceptron
  • History of Neural networks
  • Activation functions
  • Sigmoid
  • Relu
  • Softmax
  • Leaky Relu
  • Tanh
  • Gradient Descent
  • Learning Rate and tuning
  • Optimization functions
  • Back propagation and chain rule
  • Fully connected layer
  • Cross entropy
  • Weight Initialization
  • Deep L-layer Neural Network
  • Forward Propagation in a Deep Network
  • Getting your Matrix Dimensions Right
  • Why Deep Representations?
  • Building Blocks of Deep Neural Networks
  • Forward and Backward Propagation
  • Parameters vs Hyperparameters
  • What is Artificial Neural Networks
  • Machine Learning Vs Artificial Neural Networks
  • History of ANN
  • Building Blocks
  • Network Topology
  • Evaluating the ANN
  • Improving and tuning the ANN
  • Introduction to Convolutional Neural Networks
  • CNN Applications
  • Architecture of a Convolutional Neural Network
  • Convolution and Pooling layers in a CNN
  • Understanding and Visualizing CNN
  • Transfer Learning and Fine-tuning Convolutional Neural Networks
  • Intro to RNN Model
  • Application use cases of RNN
  • Modelling sequences
  • Training RNNs with Backpropagation
  • Long Short-Term Memory (LSTM)
  • Recursive Neural Tensor Network Theory
  • Recurrent Neural Network Model
  • Time Series Forecasting
  • Practical Aspects of Deep Learning
  • Discover and experiment with a variety of different initialization methods, apply L2 regularisation and dropout to avoid model overfitting, then apply gradient checking to identify errors in a fraud detection model.
  • Train / Dev / Test sets
  • Bias / Variance
  • Basic Recipe for Machine Learning
  • Regularisation
  • Why Regularization Reduces Overfitting?
  • Dropout Regularisation
  • Understanding Dropout
  • Other Regularization Methods
  • Mini-batch Gradient Descent
  • Understanding Mini-batch Gradient Descent
  • Exponentially Weighted Averages
  • Understanding Exponentially Weighted Averages
  • Bias Correction in Exponentially Weighted Averages
  • Gradient Descent with Momentum
Live Online Training (Duration : 40 Hours)
We Offer :
  • 1-on-1 Public - Select your own start date. Other students can be merged.
  • 1-on-1 Private - Select your own start date. You will be the only student in the class.

2400 + If you accept merging of other students. Per Participant & excluding VAT/GST
4 Hours
8 Hours
Week Days

Start Time : At any time

12 AM
12 PM

1-On-1 Training is Guaranteed to Run (GTR)
Group Training
1750 Per Participant & excluding VAT/GST
02 - 06 Oct
09:00 AM - 05:00 PM CST
(8 Hours/Day)
06 - 10 Nov
09:00 AM - 05:00 PM CST
(8 Hours/Day)
Course Prerequisites
• Prior experience in Python programming
• Understanding of basic high school level Mathematics
• Knowledge in concepts of Machine Learning
• Familiarity with basic statistics and probability
• Prior exposure to Neural Networks
• Basic understanding of algorithms and computational complexity.

Mastering in Deep Learning Certification Training Overview

Mastering in Deep Learning certification training equips participants with fundamental knowledge and practical expertise in Deep Learning algorithms and tools. The course generally covers topics such as convolutional neural networks, artificial neural networks, deep reinforcement learning, restricted Boltzmann machines, and Long Short-Term Memory (LSTM). It also includes extensive hands-on training in various software libraries and frameworks used for Deep Learning, enabling participants to develop advanced artificial intelligence applications.

Why Should You Learn Mastering in Deep Learning?

Mastering a Deep Learning course in stats equips learners with advanced technical skills to design, implement and analyze deep learning models. It allows for greater career opportunities in data science, AI, machine learning, and increases employability in high-growth, high-pay tech sectors.

Target Audience for Mastering in Deep Learning Certification Training

• AI aspirants who already have basic understanding of programming and AI concepts
• Software engineers willing to transition into the AI industry
• Data Analysts and Scientists aiming to harness deep learning in their data processing tasks
• Machine Learning engineers seeking to strengthen their knowledge in deep learning
• Project managers leading AI or machine learning teams

Why Choose Koenig for Mastering in Deep Learning Certification Training?

- Certified Instructors: Koenig Solutions has a team of certified instructors ensuring top-tier quality training.
- Boost Your Career: Their courses are designed to enhance professional skills and boost career growth.
- Customized Training Programs: They provide customized training programs meeting individual learner's needs.
- Destination Training: They offer destination training facilities.
- Affordable Pricing: The institute offers high-quality learning at competitive pricing.
- Top Training Institute: Renowned globally as a top IT training institute.
- Flexible Dates: They offer flexible dates for each course making learning convenient.
- Instructor-Led Online Training: All programs are instructor-led, providing real-time learning experience.
- Wide Range of Courses: Koenig houses a broad array of deep learning courses.
- Accredited Training: Their training programs are accredited by recognized global bodies.

Mastering in Deep Learning Skills Measured

After completing Mastering in Deep Learning certification training, an individual can gain skills like understanding deep learning algorithms, neural network architectures, backpropagation and stochastic gradient descent. They can also learn to tune deep learning models, use GPUs for training models efficiently, apply deep learning principles to natural language processing and computer vision applications, use libraries like TensorFlow, Keras, and PyTorch, build, train and deploy complex deep learning models, and understand AI and deep learning's future impacts.

Top Companies Hiring Mastering in Deep Learning Certified Professionals

Top companies like Google, Facebook, Microsoft, IBM, and Amazon are routinely hiring professionals with a Master's in Deep Learning. These tech giants value expertise in artificial intelligence, machine learning, neural networks and require highly skilled individuals to help innovate and advance their technologies. Other prominent companies include LinkedIn, Intel and Nvidia.

Learning Objectives - What you will Learn in this Mastering in Deep Learning Course?

The primary learning objectives of a Mastering in Deep Learning course include understanding the fundamental concepts and algorithms of deep learning. Participants are expected to learn various models such as convolutional neural networks, recurrent neural networks and autoencoders. Additionally, they should acquire the skill of implementing and training these models using popular deep learning frameworks like TensorFlow or Keras. Ultimately, the course aims to equip participants with the ability to apply deep learning techniques to real-world problems, interpret the results, and craft innovative solutions. They should also be capable of staying up-to-date with the latest research in this constantly evolving field.
Student Name Feedback
Nilesh Padbidri
United States
A1. I am very impressed by the thoroughness and completeness of Shifali's knowledge, her commitment to ensuring that I understand every single detail. What is commendable is she did this, when she was keeping unwell. Seldom do you come across people with this level of potential. I am certain that Shifali is meant for much bigger things and I wish her all the best.
John Marko
United States
A1. this is my second course with Nidhi, what I can say to her is that her expertise and enthusiasm have made a lasting impact on me. Each session with her has been enlightening, and her genuine passion for teaching shines through in every lesson. her ability to break down complex topics and make them comprehensible is truly commendable. I feel privileged to have been trained by someone of her calibre. I will always remember the value_counts() function and make it my favoured. I wish her all the best and encourage her to keep doing what she is doing because she is not just teaching; she is inspiring and transforming lives.


Yes, we do.
Schedule for Group Training is decided by Koenig. Schedule for 1-on-1 is decided by you.
In 1 on 1 Public you can select your own schedule, other students can be merged. Choose 1-on-1 if published schedule doesn't meet your requirement. If you want a private session, opt for 1-on-1 Private.
Duration of Ultra-Fast Track is 50% of the duration of the Standard Track. Yes(course content is same).
1-on-1 Public - Select your start date. Other students can be merged. 1-on-1 Private - Select your start date. You will be the only student in the class.
Yes, course requiring practical include hands-on labs.
You can buy online from the page by clicking on "Buy Now". You can view alternate payment method on payment options page.
Yes, you can pay from the course page and flexi page.
Yes, the site is secure by utilizing Secure Sockets Layer (SSL) Technology. SSL technology enables the encryption of sensitive information during online transactions. We use the highest assurance SSL/TLS certificate, which ensures that no unauthorized person can get to your sensitive payment data over the web.
We use the best standards in Internet security. Any data retained is not shared with third parties.
You can request a refund if you do not wish to enroll in the course.
To receive an acknowledgment of your online payment, you should have a valid email address. At the point when you enter your name, Visa, and other data, you have the option of entering your email address. Would it be a good idea for you to decide to enter your email address, confirmation of your payment will be emailed to you.
After you submit your payment, you will land on the payment confirmation screen. It contains your payment confirmation message. You will likewise get a confirmation email after your transaction is submitted.
We do accept all major credit cards from Visa, Mastercard, American Express, and Discover.
Credit card transactions normally take 48 hours to settle. Approval is given right away; however, it takes 48 hours for the money to be moved.
Yes, we do accept partial payments, you may use one payment method for part of the transaction and another payment method for other parts of the transaction.
Yes, if we have an office in your city.
Yes, we do offer corporate training More details
Yes, we do.
Yes, we also offer weekend classes.
Yes, Koenig follows a BYOL(Bring Your Own Laptop) policy.
It is recommended but not mandatory. Being acquainted with the basic course material will enable you and the trainer to move at a desired pace during classes. You can access courseware for most vendors.
Yes, this is our official email address which we use if a recipient is not able to receive emails from our @koenig-solutions.com email address.
Buy-Now. Pay-Later option is available using credit card in USA and India only.
You will receive the letter of course attendance post training completion via learning enhancement tool after registration.
Yes you can.
Yes, we do. For details go to flexi
You can pay through debit/credit card or bank wire transfer.
Dubai, London, Sydney, Singapore, New York, Delhi, Goa, Bangalore, Chennai and Gurugram.
Yes you can request your customer experience manager for the same.
Yes of course. 100% refund if training not upto your satisfaction.

Prices & Payments

Yes of course.
Yes, We are

Travel and Visa

Yes we do after your registration for course.

Food and Beverages



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“It is an interesting story and dates back half a century. My father started a manufacturing business in India in the 1960's for import substitute electromechanical components such as microswitches. German and Japanese goods were held in high esteem so he named his company Essen Deinki (Essen is a well known industrial town in Germany and Deinki is Japanese for electric company). His products were very good quality and the fact that they sounded German and Japanese also helped. He did quite well. In 1970s he branched out into electronic products and again looked for a German name. This time he chose Koenig, and Koenig Electronics was born. In 1990s after graduating from college I was looking for a name for my company and Koenig Solutions sounded just right. Initially we had marketed under the brand of Digital Equipment Corporation but DEC went out of business and we switched to the Koenig name. Koenig is difficult to pronounce and marketeers said it is not a good choice for a B2C brand. But it has proven lucky for us.” – Says Rohit Aggarwal (Founder and CEO - Koenig Solutions)
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