Artificial Intelligence refers to computer systems that can mimic human intelligence. AI is demonstrated when a task, formerly performed by a human and thought of as requiring the ability to learn, reason, and solve problems, can now be done by a machine. There are many types of artificial intelligence that are used today. For example, when a user logs into a movie streaming service, the recommendations for what to watch next are generated by artificial intelligence that uses algorithms to find content similar to what the user has previously watched. Another example is an autonomous vehicle, which is able to perceive its surroundings and make decisions in order to safely reach its destination without human intervention.
The field of artificial intelligence encompasses computer science, natural language processing, coding, mathematics, data science, and many other disciplines. An AI tutorial or free artificial intelligence course for beginners can teach learners:
The uses of AI for businesses and society
Ethics issues related to AI
AI programming for intelligent agents such as search algorithms, games, and logic problems
Syllabus of Artificial Intelligence Course
Introduction
- What is Data Science?
- What is Machine Learning?
- What is Deep Learning?
- What is AI?
- Data Analytics & it’s types
Hands-on:
How to implement linear regression and logistic regression using Deep learning
Understanding the Neural network with TensorFlow:
Objective:
In this module, you will get an idea about the deep learning structure and how we can build it using Neurons (Perceptron). You will familiarize yourself with different activation functions and have a brief introduction to the TensorFlow framework.
- Structure and working of Deep Learning
- Detailed explanation about Perceptron
- Different Activation functions
- Introduction to TensorFlow
- What is the computational graph?
- Basic TensorFlow coding and graph visualization
- Brief introduction about Variables, Constants and Place Holders
- Creating a simple TensorFlow model
Hands-on:
Build a classification model using TensorFlow
Deep dive into Neural Network with TensorFlow:
Objective:
In this module, you will be learning about Deep Neural Networks and how does it work. Also, you will get more understanding of forwarding and backward propagation.
- Different layers in the Neural network
- Understanding Neural Network in detail
- Introduction to Multi-layer Perceptron
- What is Forward propagation and Backpropagation?
- Build a Multi-layer perceptron model using TensorFlow
- Familiarise in using Tensor Board
Hands-on:
Build a deep neural network to classify digits in MNIST dataset
Master Deep Networks:
In this module, you will get more hands-on for the TensorFlow framework. You will get to know more details about the data flow in TensorFlow.
- What is a Deep Neural Network?
- How Deep Neural Network helps to increase accuracy?
- Understanding the working of Deep Neural Network
- What is Weight and Bias, how it is getting updated?
- How gradient descent is useful to update parameters?
- Types of Deep Networks
Hands-on:
Building a classification model using a Multi-layered perceptron.
Convolutional Neural Network(CNN):
Objective:
In this module, you will be learning what convolutional neural network is and how it is different from Feedforward neural network. Also, you will get an understanding of various layers in the Convolutional Neural Network and what are the real-time applications of CNN.
- Introduction to CNN
- Advantage of CNN over other Neural Networks
- Applications of CNN
- Architecture of CNN
- Different layers and its use to build a CNN model
- Real-time use cases of CNN
Hands-on:
Building an Image classification model using CNN
Upcoming Batch Schedule for Data Science with Python
| Date | Dayz | Time |
|---|---|---|
|
25-02-2023 |
Mon - Sat
|
07:00 AM
(Class 1Hr - 1:30Hrs) / Per Session |
|
01-03-2023 |
Mon - Sat
|
07:00 AM
(Class 1Hr - 1:30Hrs) / Per Session |
|
07-03-2023 |
Mon - Sat
|
07:00 AM
(Class 1Hr - 1:30Hrs) / Per Session |
Trainer Profile of Deep Learning
Our Trainers provide complete freedom to the students, to explore the subject and learn based on real-time examples. Our trainers help the candidates in completing their projects and even prepare them for interview questions and answers. Candidates are free to ask any questions at any time.
- More than 7+ Years of Experience.
- Trained more than 2000+ students in a year.
- Strong Theoretical & Practical Knowledge.
- Certified Professionals with High Grade.
- Well connected with Hiring HRs in multinational companies.
- Expert level Subject Knowledge and fully up-to-date on real-world industry applications.
- Trainers have Experienced on multiple real-time projects in their Industries.
Deep Learning Exams & Certification
We provide after completion of the theoretical and practical sessions to students. Our certification at Stormsofts Technology is accredited by many companies. It increases the value of your resume and you can attain leading job posts with the help of this certification in leading MNC’s . The certification is only provided after the successful completion of our training and practical-based projects.
College Training
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Key Features of Deep Learning
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