Deep Learning & Reinforcement Learning Training

Private Training
Online Training

Take a well-balanced mixture of theory and practice to start building and applying deep neural networks and ML models (with Keras, TensorFlow) from the 1st training day.

A group from 5 engineers, flexible price, preferable time, and location.

Deep Learning & Reinforcement Learning Training

Duration

5 days

Format

Tailor-made,

Delivering

ONLINE, Instructor-led

The course was especially tailored for

  • Software Engineers
  • Data Scientists

The course covers

  • This five-day hands-on Deep learning and Reinforcement learning course is designed for all those seeking a better understanding and knowledge of the major technology trends driving data science.
  • Attendees will get a clear understanding of the core machine learning concepts, as well as Deep Learning and Reinforcement learning techniques and engineering solutions for daily usage. You will go through the complete process of building machine learning systems, from data understanding to modeling.
  • During hands-on labs, accompanying each theoretical unit, you will gain experience in building and applying deep neural networks and machine learning models with such widely used frameworks as Keras, TensorFlow, and scikit-learn.
  • At the end of the course, the participants will be able to design working scripts that can be used as a basis for creating algorithms to address business-specific challenges.

Why enroll

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1
2
3
4
5+

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The price rises closer to the type of training. Have time to buy now!

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The course could be tailored to suit your needs and objectives. It can also be delivered on your premises if preferred.

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Special price

From - To

Number of Delegates

The course could be tailored to suit your needs and objectives. It can also be delivered on your premises if preferred.

Price

${{privatePriceString}}

${{privatePriceStringPerson}} per person

Special price

Training program

Day 1

  • Introduction to deep learning

    This is an introduction to the Deep Learning methods for Machine Learning tasks. During this day, we’ll look at surprisingly strong machine learning techniques that have become really popular recently and will cover the following topics:

    • Structure of neural networks, feedforward neural networks
    • A mechanism for learning neural networks
    • Means of neural network learning process control

Day 2

  • Convolutional neural networks

    Image processing benefitted drastically from Deep Learning. The main architecture for these tasks is Convolutional Neural Network. Topics for the day will include:

    • Image features and representation learning
    • A convolution layer and a deep convolutional network
    • Supporting layers for convolutional neural networks
    • State-of-the-art architectures for image processing
    • Transfer learning and fine tuning

Day 3

  • Recurrent neural networks

    This day is dedicated to the architecture of neural networks that allow to work with sequential data, most notably, texts. During this day we will cover:

    • Examples of sequential data and related machine learning tasks
    • The vanilla recurrent neural network architecture and its limitations
    • The advanced recurrent neural network layers architecture (LSTM, GRU)

Day 4

  • Reinforcement learning introduction

    This day is dedicated to establishing a theoretical base of Reinforcement Learning methods. We’ll also look at the most common solutions for Reinforcement Learning that could be used to address NIWC tasks:

    • Theoretical overview of reinforcement learning task
    • Multi-Armed Bandits (acquiring new knowledge and optimizing decisions based on existing knowledge, balance these tasks to maximize their total value)
    • Markov Decision Processes (mathematical framework for modeling decision making process in situations where outcomes are partly random and partly under the control of a decision maker)
    • Temporal-Difference Methods (reinforcement learning principle that enables online learning from actions directly). Q-learning (method that estimates value of taking an action in different situations)

Day 5

  • Deep reinforcement learning

    Deep Reinforcement Learning combines principles from Reinforcement Learning with Deep Learning. Resulting combination is allowing us to build algorithms that solve complex tasks in different environments.

    • Limitations of basic Reinforcement Learning algorithms (and possible tricks to extend the capabilities for classic methods of Reinforcement Learning)
    • Deep Q-learning (adaptation of Q-learning algorithm to tackle more complex environments)
    • Actor-Critic models (addition to Agent scheme that allows to build more effective algorithms)

Still have questions? Review our FAQ section or feel free to contact us.

Still have questions? Review our FAQ section or feel free to contact us.

Prerequisites

01

Minimum group size - 5 persons. Also available for large groups.

02

This course assumes that you have some basic knowledge of Machine Learning concepts. That's not obligatory, but useful to get familiarised with calculus, linear algebra and applied statistics to understand the theory behind the algorithms.

{{eventName}}

Select location

When

Number of participants

1
2
3
4
5+

Total price

${{commonPriceString}}

The price rises closer to the type of training. Have time to buy now!

From - To

Number of Delegates

The course could be tailored to suit your needs and objectives. It can also be delivered on your premises if preferred.

Price

${{privatePriceString}}

${{privatePriceStringPerson}} per person

Special price

From - To

Number of Delegates

The course could be tailored to suit your needs and objectives. It can also be delivered on your premises if preferred.

Price

${{privatePriceString}}

${{privatePriceStringPerson}} per person

Special price

Training from authorized Partner

Meet us

Get updates on upcoming events and new courses, discounts and special offers

Our attendees

Here is what our attendees say about us

/
01

“Biggest value of the course? Combination of conceptual and practical contents. Showing the state-of-the art achievements and hence developing a feeling what can be achieved with DNN”

Arpad Rozsas

Neural Networks and Deep Learning training, Madrid

02

“I enjoyed the class and learned a lot even though there was so much content jammed into a very small time. The most enjoyable was deep neural nets and seeing some of the largest example. The most valuable thing professionally will probably be the classification clustering that I have learned K-NN probably”

Mark Foresta

Machine Learning training, Washington DC

03

“Great experience! Very knowledgeable and friendly trainers. Biggest value of the course - practical examples/issues the trainers provided based on their experience”

Ramesh Balasubramanian

Machine and Deep Learning Training, San Diego

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Frequently asked questions

Did not find the answer to your question? Drop us a line at training@altoros.com

  • What are the prerequisites?

    At least minimum experience in programming is enough to proceed!

  • What are the available payment options?

    You can pay via all major credit cards (including Visa, American Express, MasterCard, Discover, and more) or PayPal. If you would like to get an invoice for your company to pay for this training, please email to training@altoros.com and provide us with the following info: Name of your Company/Division which you would like to be invoiced; Name of the person the invoice should be addressed to; Mailing address; Purchase order # to put on the invoice (if required by your company).

  • Do you offer group discounts?

    Yes, we also offer a discount for groups of 5 or more people who register together.

  • I bought a ticket but occasionally should miss training.

    Please, email to training@altoros.com. Our team will provide you information about the nearest date to your location.

  • What services do you offer after the training?

    We'd be glad to provide you with: Post-training support from our trainers to cover the questions that you or your team might have; Advanced training options or classes on a different domain to widen your expertise and technical skillset (Kubernetes, Cloud Foundry, Artificial Intelligence / Machine Learning); Customized consulting services for project delivery.

  • Will I get a certificate after completion?

    Yes! Once you have completed our training, you will be issued a certificate that you can print or add to your LinkedIn profile for others to see. Note: the certificate does not represent official academic credit.

  • Do you offer discounts for individuals?

    Yes, we offer discounts of up to 10% off for early birds who register for the training in advance. Each discount tier has a limited number of seats and all of our discounts are available in limited quantities. Once we sell out of our discounted seats, we move to full price.

  • What size are the groups?

    The standard group size is 8-10 people. Small class sizes provide students unparalleled access to instructors, who are seasoned industry veterans with experience building and deploying full-scale AI solutions. Note: The class is contingent upon having 7+ attendees. If there aren’t enough students, we will offer you to attend the class in a different location or date. That is also the reason why we ask not to buy flight tickets before the class is confirmed.

  • I need to travel to participate in training. Do you help with visa?

    We do not participate in the process of application for visa. However, you can use a confirmation that you have registered for our class and bought the ticket for it. This should support your visa application. If your application is declined, we will refund the ticket.

  • Why should I trust Altoros Training?

    Being a Google Gold Partner and AI Builder Partner Altoros delivers AI projects to the organizations that operate in various markets, like banking and finance, insurance, manufacturing, and others. An experienced AI team already helped 14 companies with machine learning adoption and delivering competitive advantage by utilizing the benefits of the technology. More than 500 people all over the world were trained and adopted the knowledge of our experts.

Contact us

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Ryan Meharg

Ryan Meharg

Technical Director

ryan.m@altoros.com650 265-2266

4900 Hopyard Rd. Suite 100 Pleasanton, CA 94588