What's Inside?


Complete Neural Networks and Deep Learning course for TensorFlow and Keras.

This course is designed to help you learn machine learning with statistical modeling and visualization of data. Also, it covers the basic techniques of deep learning. All you need to do is invest your 7-hours in this Python-based Tensorflow and Keras frameworks of Neural Network, machine learning, and Deep Learning Boot Camp.



Why should you enroll in this course? 

There are various reasons you might need this course for. First, this TensorFlow and Keras-based course is designed to provide you (learners) complete practical guide on neural networks and its techniques in python using the Tensorflow and Keras frameworks.

Moreover, with this course, you never need to purchase other books to make your concepts strong. Since this course is wholesome to understand neural networks with TensorFlow and Keras frameworks, do not worry about any concept that most instructors forget.


Tensorflow and Keras are the most crucial frameworks of deep learning.

Tensorflow is an open-source library that is used for implementing boundless tactics in machine learning. These tactics are implemented through its API's both low and high-level. On the other hand, Keras is a neural network library that provides only high-level neural APIs powered by Python. Between these two frameworks, Keras is more user-friendly.


I believe, in this age of machine learning, neural networks, and big data, TensorFlow and Keras frameworks is the most demanded platform among reputable companies. They use TensorFlow and Keras frameworks to expose the information that is residing throughout the world and revolutionize the neural network industry.


Through my avalanche of data, you can provide your company with a remarkable competitive edge. Also, you can boost your career to the next level once you learned how to store, filter, manage and manipulate data in Python's anaconda, Keras and Tensorflow.


My Promise to you!

You can become a pro in the practical world of TensorFlow and neural networks with Keras, which resides under machine learning and deep learning, once you fulfill the course requirements.


Unlike other courses, this course will help you dig out every feature of statistical modeling and give you the grounding experience of TensorFlow that you can apply in the practical world.

What will you learn in this course?

Our seven sections in this course address every aspect of neural networks, and machine learning in python-based TensorFlow and Keras frameworks. This course will cover the following:

  • A complete introduction to python-based anaconda, Keras, and TensorFlow-driven data science, machine learning, and neural networks.
  • Interaction with python Jupyter notebooks and Libraries of Keras and TensorFlow to implement AI-based techniques of machine learning, and neural networks
  • Presentation of Tensorflow and Keras installation.
  • Interaction with basic packages and frameworks of python used in Keras and TensorFlow
  • Introduction to Pandas and Numpy libraries
  • Understanding of basic syntax and visualization in TensorFlow environment
  • Statistical modeling in Tensorflow frameworks
  • Machine learning in both Supervised and Unsupervised Learning under Keras and Tensorflow frameworks
  • Understanding structures of artificial neural networks and deep learning structures

But wait! My course is not just an average course!

In this course, you will absorb the most powerful hacks that work behind Keras and Tensorflow techniques associated with machine learning, deep learning, and neural networks.

I will help you to get started with valuable concepts and techniques in TensorFlow and Keras neural networks. As mentioned earlier, I have used the most simple, easy-to-understand, and straightforward methods to address every concept of TensorFlow and keras frameworks along with python libraries.

This course will be the proven ultimate guide for you that will help you to implement the machine learning and deep learning techniques in the real world. No matter, what type of data you want to interpret.

At the end of this course, you will be able to use TensorFlow and Keras frameworks such as NumPy, matplotlib, and pandas in different scenarios and gain fluency in Tensorflow. What is more?

Deep conceptualization of python's statistical modeling is not going anywhere if you invest your time in deep learning.

Even, I assure you that my course will cover other deep learning models, too. For example, I have added lectures that cover Convolution Neural network (CNN), Long Short Term Memory Networks (LSTMs), Generative Adversarial Networks (GANs), Multilayer Perceptrons (MLPs) and more.



All-In-One neural networks Course in Python

As I said earlier, this course is wholesome. In TensorFlow and Keras, you will learn all aspects of deep learning such as visualization, stats, neural networks, image recognition and mining of data.

The motivation behind this course is the practice, which students are lacking these days on the real-time interpretations. My vision is to provide students with real-world data and let them interpret it. Students will be able to analyze their own projects in order to impress reputable employers with their skill sets under neural networks.

Finally, this course is practical. In this course, you will be spending time dealing with theoretical as well as practical concepts. Around 30%, of course, is based on theoretical concepts, and 70%, of course, is based on practice where students will implement deep learning techniques to interpret and analyze probable outcomes. In every lecture, our video will help you to learn the technical concepts of your own projects.


Frequently Asked Questions (FAQs)


How do I access the course?

All you need is a modern browser such as Chrome, Firefox, or Internet Explorer and you will be able to access the course from any computer, tablet, or mobile device.

 

Is there a specific time duration to complete this course?

Learning with Eskills Academy is super easy. No limitation on-time duration so you learn easily at your own pace and convenience.

 

Do I get a certificate?

Yes, when you complete the course you will receive a certificate of completion, which you can happily add to your resume or LinkedIn profile.

 

In what cases will I be eligible for a refund?

All Eskills Academy courses come with Teachable backed 30-day money-back guarantee. If you are not satisfied with the purchased course, refunds are applicable as per our terms mentioned on the website.


Other FAQ’s

What prior knowledge do I need to attend the teacher-led class?

At least six months of professional PC configuration and troubleshooting experience.


How can I access my course materials if I choose this method?

Upon receipt of payment, Eskills will send you an email with all the links and information you need to get started.


What content on-demand will I get?

You will have access to official CompTIA On-Demand content that is constantly updated so you can prepare for your A + exam and stay informed of any content changes during your subscription period.


What laboratories do I have access to?

Gains access to [enter number] preconfigured A + curriculum labs.


How many practice tests are included?

 4A + accredited practice exams are included.


How do I plan my teacher-led training?

As soon as payment has been received, you will receive the details of your training package with unlimited access by email. At this point, you can call or email our customer service team to help you register for the event date you have chosen.

Student Feedback & Reviews

Adam Meiger

Online courses are a blessing for me. Eskills Academy gave me so many options to learn in my free time and excel in my performance at work.


Zeina Wessam

The course was fun to learn and there was no pressure at all with timings. I kept learning at my own pace and now using the lessons in my practical life.


Marzenna Guimara

I was looking for courses to refresh some basics and get some tips on doing things in a new way. The courses are well taught and I can now practice them without much help.