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Advanced Interactive
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Hands On Training
Updated Content
Learning Paths
Mentors
Advanced Interactive
Artificial Intelligence (AI) refers to systems of human intelligence processes by machines engineered to assume like human beings and also to replicate their behaviour. The phrase may also apply to any computer system that demonstrates attributes similar to a human mind, like learning and problem-solving.A subset of artificial intelligence is machine learning, that also pertains to the framework that computer programmes can enable learning from and adapt to new data without the assistance of humans. Deep learning methods support faster learning through the uptake of immense quantities of large amounts of data, such as text, images or video.
HKR trainings offers a complete Artificial Intelligence program that helps you collaborate on cutting-edge Artificial Intelligence technology today (AI). As part of this best AI training, you will understand different aspects of artificial neural networks, supervised and unsupervised learning, logistic regression with neural network thinking, binary classification, vectorization, Python for scripting, machine learning applications, etc. Our sophisticated learning paradigm helps to increase and sharpen your skills in this competitive field.You will experience good support and real-time project assistance during the training period. Enroll now to make the most of your Artificial Intelligence certification training in Hyderabad.
To apply for the Artificial Intelligence Training in Hyderabad, you need to either:
We at HKR Trainings provides an optimized Artificial Intelligence course structure that helps the individual to gain the concepts easily.
Now lets explore one module after one in detail.
1.1 Field of machine learning, its impact on the field of artificial intelligence
1.2 The benefits of machine learning w.r.t. Traditional methodologies
1.3 Deep learning introduction and how it is different from all other machine learning methods
1.4 Classification and regression in supervised learning
1.5 Clustering and association in unsupervised learning, algorithms that are used in these categories
1.6 Introduction to ai and neural networks
1.7 Machine learning concepts
1.8 Supervised learning with neural networks
1.9 Fundamentals of statistics, hypothesis testing, probability distributions, and hidden markov models.
2.1 Multi-layer network introduction, regularization, deep neural networks
2.2 Multi-layer perceptron
2.3 Overfitting and capacity
2.4 Neural network hyperparameters, logic gates
2.5 Different activation functions used in neural networks, including relu, softmax, sigmoid and hyperbolic functions
2.6 Back propagation, forward propagation, convergence, hyperparameters, and overfitting.
3.1 Various methods that are used to train artificial neural networks
3.2 Perceptron learning rule, gradient descent rule, tuning the learning rate, regularization techniques, optimization techniques
3.3 Stochastic process, vanishing gradients, transfer learning, regression techniques,
3.4 Lasso l1 and ridge l2, unsupervised pre-training, Xavier initialization.
4.1 Understanding how deep learning works
4.2 Activation functions, illustrating perceptron, perceptron training
4.3 multi-layer perceptron, key parameters of perceptron;
4.4 Tensorflow introduction and its open-source software library that is used to design, create and train
4.5 Deep learning models followed by google’s tensor processing unit (tpu) programmable ai
4.6 Python libraries in tensorflow, code basics, variables, constants, placeholders
4.7 Graph visualization, use-case implementation, keras, and more.
5.1 Keras high-level neural network for working on top of tensorflow
5.2 Defining complex multi-output models
5.3 Composing models using keras
5.3 Sequential and functional composition, batch normalization
5.4 Deploying keras with tensorboard, and neural network training process customization.
6.1 Using tflearn api to implement neural networks
6.2 Defining and composing models, and deploying tensorboard
7.1 Mapping the human mind with deep neural networks (dnns)
7.2 Several building blocks of artificial neural networks (anns)
7.3 The architecture of dnn and its building blocks
7.4 Reinforcement learning in dnn concepts, various parameters, layers, and optimization algorithms in dnn, and activation functions.
8.1 What is a convolutional neural network?
8.2 Understanding the architecture and use-cases of cnn
8.3‘What is a pooling layer?’ how to visualize using cnn
8.4 How to fine-tune a convolutional neural network
8.5 What is transfer learning?
8.6 Understanding recurrent neural networks, kernel filter, feature maps, and pooling, and deploying convolutional neural networks in tensorflow.
9.1 Introduction to the rnn model
9.2 Use cases of rnn, modeling sequences
9.3 Rnns with back propagation
9.4 Long short-term memory (lstm)
9.5 Recursive neural tensor network theory, the basic rnn cell, unfolded rnn, dynamic rnn
9.6 Time-series predictions.
10.1 Gpu’s introduction, ‘how are they different from cpus?,’ the significance of gpus
10.2 Deep learning networks, forward pass and backward pass training techniques
10.3 Gpu constituent with simpler core and concurrent hardware.
11.1 Introduction rbm and autoencoders
11.2 Deploying rbm for deep neural networks, using rbm for collaborative filtering
11.3 Autoencoders features and applications of autoencoders.
12.1 Image processing
12.2 Natural language processing (nlp) – Speech recognition, and video analytics.
13.1 Automated conversation bots leveraging any of the following descriptive techniques: Ibm watson, Microsoft’s luis, Open–closed domain bots,
13.2 Generative model, and the sequence to sequence model (lstm).
In this module, all the discussed modules are summarized again.
In this module, at the end of the course, you will be working on two real time projects for gaining practical experience, conduct mock interviews to evaluate your learned skills, Provides free course materials, frequently ask interview questions and answers, advanced AI tutorials, community question and answers, and also helps in preparing the resumes, etc.
Description: Amazon, one of largest US-based e-commerce companies, lists compiled products of the same category to customers based..... on their activities and reviews of other similar products. Amazon would like to enhance this recommender system by predicting ratings for non-rated products and adding them to the recommendations accordingly. Read more
Description: Comcast, one of the leading US-based global telecommunications companies, aims to better customer experience by speci.....fically focusing on problem areas that decrease consumer satisfaction, if any. The company is also looking for major objectives that can be enacted to provide the best customer experience. Read more
The primary aim of this course is to familiarise you with all facets of AI so that you can reach your goal as an artificial intelligence engineer. Some of the many topics/modules that you will discover in the programme are:
With demand for AI in a wide range of industries, HKR trainings AI certification course is well suited to a variety of roles and disciplines, including:
The candidates who wish to learn or build their career can take up Artificial Intelligence training in Hyderabad. Basic understanding of statistics and python programming is an added advantage to take up this AI training.
To commence your Artificial Intelligence training course in Hyderabad, people therefore need to check with the perfect institute which really provides information. Before moving ahead with any training, accept advice from the professionals that have already experienced the course. We at HKR in Hyderabad, with a squad of industry experts, are ready to fulfil your future career in order to get a job in the company you want.
Right away after the completion of the course, that is preceded by the assignments and tasks of real-time projects, HKR programme gives you a certificate for completing the course. This certification distinguishes you from other non-certified peers and also encourages to get a job at any company in Hyderabad very easily.
The Artificial Intelligence certified professionals at HKR trainings in Hyderabad deliver the lectures to the individuals to unleash their abilities in this technology.
The benefits you can gain upon the completion of the certification are , you will be given higher preference for competitive jobs related to analytics.
Undoubtedly, the HKR training experts provide you with incredible job help facilities, but not really the job. They would then direct, support and help to strengthen your potential development. However, your job will be premised on your skills identified in the recruitment process and the criteria of the hiring manager.
Each and every class is recorded so if you missed any class you can review the recordings and clarify any doubts with the trainer in next class.
Yes, we don’t assure 100% placement assistance. We are tied up with some corporate companies so when they have a requirement we send your profiles to them.
Yes, we provide demo before starting any training in which you can clear all your doubts before starting training.
Our trainers are real time experts who are presently working on particular platform on which they are providing training.
You can call our customer care 24/7
Max of the students get satisfied with our training, if you are not then we provide a specialised training in return.
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