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Artificial Intelligence Training?

Artificial Intelligence
Training With Placement

Trained Candidates
+ 15000
Training Duration
+ 65 Hrs
Assignment Duration
+ 30 hrs
Corporate Trainings Conducted
+ 14

Why Ascent Software for Artificial Intelligence Training ?

Who Can Do This Course ?

Training Methodology

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Artificial Intelligence- Syllabus

Best-in-industry, strategically designed Course Content, Projects, Class Sessions to
accomplish the changing requirement of market

  • Field of Machine Learning and its impact on the field of Artificial Intelligence
  • The benefits of Machine Learning w.r.t. traditional methodologies
  • Deep Learning introduction and how it is different from all other Machine Learning methods
  • Classification and regression in supervised learning
  • Clustering and association in unsupervised learning and the algorithms that are used in these categories
  • Introduction to AI and neural networks
  • Machine Learning concepts
  • Supervised learning with neural networks
  • Fundamentals of statistics, hypothesis testing, probability distributions, and hidden Markov models
  • Multi-layered networks introduction, regularization, and deep neural networks
  • Multi-layer perceptron
  • Overfitting and capacity
  • Neural network hyperparameters and logic gates
  • Different activation functions used in neural networks, including ReLU, Softmax, Sigmoid, and hyperbolic functions
  • Backpropagation, forward propagation, convergence, hyperparameters, and overfitting
  • Various methods that are used to train artificial neural networks
  • Perceptron learning rule, gradient descent rule, tuning the learning rate, regularization techniques, and optimization techniques
  • Stochastic process, vanishing gradients, transfer learning, and regression techniques
  • Understanding how Deep Learning works
  • Activation functions, illustrating perceptron, and perceptron training
  • Multi-layer perceptron and the key parameters of perceptron
  • TensorFlow introduction and its open-source software library that is used to design, create, and train
  • Deep Learning models followed by Google’s tensor processing unit (TPU) programmable AI
  • Python libraries in Tensor Flow, code basics, variables, constants, and placeholders
  • Graph visualization, use-case implementation, Keras, and more
  • Keras high-level neural network for working on top of TensorFlow
  • Defining complex multi-output models
  • Composing models using Keras
  • Sequential and functional composition and batch normalization
  • Deploying Keras with TensorBoard and neural network training process customization
  • Using TFLearn API to implement neural networks
  • Defining and composing models and deploying TensorBoard
  • Mapping the human mind with deep neural networks (DNNs)
  • Several building blocks of artificial neural networks (ANNs)
  • The architecture of DNN and its building blocks
  • Reinforcement learning in DNN concepts, various parameters, layers, optimization of algorithms in DNN, and activation functions
  • What is a convolutional neural network?
  • Understanding the architecture and use cases of CNN

 

  • What is a pooling layer? How to visualize using CNN?
  • How to fine-tune a convolutional neural network?
  • What is transfer learning?
  • Understanding recurrent neural networks, kernel filter, feature maps, and pooling, and deploying convolutional neural networks in TensorFlow
  • Introduction to the RNN model
  • Use cases of RNN and modeling sequences
  • RNNs with backpropagation
  • Long short-term memory (LSTM)
  • Recursive neural tensor network theory, the basic RNN cell, unfolded RNN, and dynamic RNN
  • Time-series predictions
  • GPU introduction, how it is different from CPU, and the significance of GPU
  • Deep Learning networks and forward pass and backward pass training techniques
  • GPU constituent with simpler core and concurrent hardware
  • Introduction to RBM and autoencoders
  • Deploying RBM for deep neural networks and using RBM for collaborative filtering
  • Autoencoders features and applications of autoencoders
  • Image processing
  • Natural Language Processing (NLP): Speech recognition and video analytics
  • Automated conversation bots leveraging any of the following descriptive techniques: IBM Watson, Microsoft’s Luis, and open–closed domain bots
  • Generative model and the sequence to the sequence model (LSTM)
  • Project using Artificial Intelligence
  • FAQs & Interview Preparation

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Highlights of Artificial Intelligence Training

Deep Learning &
Neural Networks

Keras & TFLearn API

Deep Learning Applications

Multilayered & Artificial Neural Networks

Autoencoders & Restricted Boltzmann Machine

DNNS, RNNS & CNNS

Chatbots &
NLP, LSTM

Live Projects & Interview Preparation

Meet Our Industry Expert Trainers

# Certified Trainers
# 10+ Years of Industry Experience
# Study Materials Designed On Real Time Problems
# Excellent Communication
# Expert Interview Panel
# Corporate Trainings

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Call us: 080-4219-1321 hours: 8am-9pm

The focus is on In-Depth Practical Knowledge with a division of 30% Theory and 70% Practical sessions. Weekdays and weekend batches are available.

We have best working professionals who are certified and have current industry knowledge to cater the needs of students.

The program is focused to make a candidate get aware of industry requirement. Classes are followed with interview questions with are very important to crack an interview.

Covering up the course a person can easily crack an interview and can work on any real time projects as focus is more on practical training.  An Industry Recognised Course Completion Certificate is a part of program.

Each topic is covered In-depth with Theory and Practical sessions. Training sessions are covered using Presentations followed by Assignments to enhance the knowledge of  students.

We have separate Internship Programs for Final Year students and Trainee Professionals which includes projects under Certified Trainer guidance . It also includes Internship Completion Certificate.

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Internship Programs

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Artificial Intelligence - Batch Schedule

Mon-Fri | 8 AM to 10 AM | 12 AM to 2 PM

Sat- Sun | 8 AM to 10 AM | 12 AM to 2 PM

Mon-Fri | 6 PM to 8 PM | 7 PM to 9 PM

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FAQ

Most frequent questions and answers

Ascent Software provides all necessary modes of training 

  • Classroom Training
  • Live Instructor LED Online Training
  • One to One training
  • Fast Track Training
  • Customized Training
  • Corporate Training

No worries. We at Ascent Software assures that a student should get full advantage of every session and if a class is missed that there is always a provision of backup class. We have different batches for the same course so the student is free to attend the same topic in any other batch within the stimulated course duration. If a student is unable to undersatnd certain topic then also the same process can be done.

A student can book a slot for free demo class as per his convenient timing. We have both classroom and online demo classes.

After completion of course a student will recieve globally recognized Ascent Software Training Institute Course Completion Certificate.

We accept all kinds of payment options. Cash, Card, NetBanking, Paytm, Google Pay, PhonePe etc.

You can call on 080-42191321 or you can enquire at hr@ascentcourses.com

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(Phone until 20:30 Hrs)
Sunday - 8:00 -14:00

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Phone: 080-42191321
Mob : 9035037886
Email: hr@ascentcourses.com

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