Deep Learning TensorFlow Training Course at DataMites

Quick Facts

particular	details
Medium of instructions English	Mode of learning Self study, Virtual Classroom +1 more	Mode of Delivery Video and Text Based

Course overview

Deep Learning - TensorFlow Training by DataMites is supported by global industry experts and saturated with the latest best practices to transform learners into deep learning experts. The workshop and Deep Learning - TensorFlow Training certification syllabus will help them learn the foundations of deep learning with TensorFlow and create an understanding of neural networks. Additionally, they will learn about Adam, BatchNorm, Dropout, Convolutional networks, LSTM, RNNs, etc.

Course and certificate fees

Fees information

₹ 60,795 ₹72,000

Deep Learning - TensorFlow Training Fees details

Fee	Amount in INR
Plans	Live Training	Blended Training	Classroom Training
Course Fee	Rs 72000	Rs 43000	Rs. 90000

certificate availability

Yes

certificate providing authority

IABAC

Who it is for

Data scientist

The Deep Learning - TensorFlow Training programme is ideally best for candidates who are:

Data scientists
Data science professionals
Analytics professionals
Professionals who are pursuing Data scientist tracks

Eligibility criteria

Education

Candidates willing to get admission in Deep Learning - TensorFlow Training must have prior knowledge of Machine Learning, Basic Python programming, and Statistics.

Certification qualifying details

Deep Learning - TensorFlow training Certification will be issued as a global IABAC certification to those who complete the course and qualify for the exam.

What you will learn

Knowledge of python Knowledge of deep learning

Deep Learning - TensorFlow Training Programme will amplify the deep learning concepts of learners. The following are the different learning outcomes:

Learn the concepts of deep learning.
Deal with all the concepts surrounding Tensorflow.
Discover how Tensorboard visualization is carried out.
They will get the experience of hands-on coding of neural networks with Tensorflow.
Learn to apply ML with Tensorflow in a case study.
Candidates will note how deep learning is different from machine learning.
Learn about clustering with the K-means concept and application.
Learners will also discover how to create operators and execute sessions
They will learn about simple models while applying reinforcement learning in TensorFlow.

The syllabus

Introduction to Deep Learning

What is a neural network?
Supervised Learning with Neural Networks - Python
How Deep Learning is different from Machine Learning

Overview of Machine Learning Concepts

What is Machine Learning?
Supervised Machine Learning algorithms
K-Nearest Neighbors (KNN) concept and application
Naive Bayes concept and application
Logistic Regression concept and application
Classification Trees concept and application
Unsupervised Machine Learning algorithms
Clustering with K-means concept and application
Hierarchical Clustering concept and application

TensorFlow Essentials

Representing tensors
Creating operators and executing with sessions
Introduction Jupyter notebook for TensorFlow coding
TensorFlow variables
Visualizing data using TensorBoard

ML Algorithm - Linear Regression in TensorFlow

Regression problems
Linear regression applications
Regularization
Available datasets
Coding Linear Regression with TensorFlow - Case study

Deep Neural Networks in TensorFlow

Basic Neural Nets
Single Hidden Layer Model
Multiple Hidden Layer Model

Convolutional Neural Networks

Introduction to Convolutional Neural Networks
Input Pipeline
Introduction to RNN, LSTM, GRU

Reinforcement Learning in Tensorflow

Concept of Reinforcement Learning
Simple model applying Reinforcement Learning in TensorFlow

Hands on Deep Learning Application with TensorFlow

Example Application - Case study
Hands-on building the Deep Learning application with TensorFlow

Admission details

Deep Learning - TensorFlow Training programme requires candidates to follow the given process for registration-

Step 1: Visit the course webpage and select “Enquire Now.”

Step 2: Enter your details and a counsellor will get in touch with you regarding the further process.

How it helps

Given the increasing popularity of TensorFlow in companies like Google, Deep Learning - TensorFlow Training certification benefits learners with real-life projects and industry-led training. Since Tensorflow is now highly preferred for deep learning and machine learning applications, Deep Learning - TensorFlow Training certification course will prove to be advantageous as experts are now switching to TensorFlow for hosting the machine learning (production level) directly to Google Cloud. They will get to use a cloud data science lab with popular platforms like R and Python.

FAQs

Can Deep Learning - TensorFlow Training Fees be paid in installments?

DataMites will require learners to pay the fee on the first day of their course but special cases will be considered. Candidates can get in touch with the team at DataMites and ask about the installment plan.

Will Deep Learning - TensorFlow Training certification exam be conducted in online or offline mode?

Candidates can appear in exams in both offline or online mode at their convenience.

What if a learner wishes to discontinue learning after paying the fee?

In case, a candidate wants to withdraw from the programme after making the fee payment, hen he/she is advised to connect with the team of DataMites. The fee refund totally depends upon the approval of management.

How will a learner receive his/her certification?

The certificate of completion will be received from the DataMites office by showing an ID proof. Alternatively, certificates can be dispatched to their address registered in the exam information sheet.

By what time will the certificates be dispatched?

Ideally, certificates take about 5-7 days to be dispatched.

Do candidates have to attempt all projects in the programme?

Candidates have the option to attempt any two projects in the entire course. They can also suggest topics to their mentor.

What are Deep Learning - TensorFlow Training certification benefits on pursuing the blended training programme?

Candidates will get access to live mentoring, one year access to e-learning portal, all-day round learner assistance, and 10 capstones, and one client project.

Do candidates have the option of pursuing more than one learning option?

Based on their preference, candidates can opt for more than one learning option.

Can candidates take the examination later?

The candidates are requested to connect with their mentor for this. Usually, it is advised to appear for exams within a span of one month of course completion but in case there is an emergency, candidates can update the same with Data Mites.