Learn - AI

Artificial Intelligence (AI)

Artificial Intelligence (AI) enables machines to perform human like tasks by learning from experience and adjust to new inputs. Computers can be trained using technologies like deep learning and natural language processing to accomplish specific tasks by processing large data and recognizing patterns in data.   Common AI examples like self-driving cars and chess playing computers is rely on these technologies.

Artificial Intelligence (AI) has revolutionized the many sectors and some of the examples:

Healthcare: AI applications in healthcare have improved diagnosis and personalized medicine.

Retail: AI enables the customers to experience virtual shopping, personalized recommendations and discussing purchase options.

Banking: AI has helped to identify fraudulent transactions and provide accurate credit scoring1.

 

LEARN – AI is the only Indian company that is an Official business partner of OpenCV

OpenCV (Open Source Computer Vision Library) is an open source computer vision and machine learning software library. OpenCV was built to provide a common infrastructure for computer vision applications and to accelerate the use of machine perception in the commercial products.

The library has more than 2500 optimized algorithms, which includes a comprehensive set of both classic and state-of-the-art computer vision and machine learning algorithms. These algorithms can be used to detect and recognize faces, identify objects, classify human actions in videos, track camera movements, track moving objects, extract 3D models of objects, produce 3D point clouds from stereo cameras, stitch images together to produce a high-resolution image of an entire scene, find similar images from an image database, follow eye movements, recognize scenery and establish markers to overlay it with augmented reality, etc.

Along with well-established companies like Google, Yahoo, Microsoft, Intel, IBM, Sony, Honda, Toyota that employ the library, there are many startups such as Applied Minds, VideoSurf, and Zeitera, that make extensive use of OpenCV.

 

Learn-AI is the official business partner of TCS iON

TCS iON™, a strategic unit of Tata Consultancy Services (TCS), a leading global IT services, consulting and business solutions organization, announced that its National Qualifier Test (NQT) will now be a common gateway test for several participating corporates for their fresher recruitment programs. This standardized test will provide candidates with access to open positions at multiple corporates, while helping corporates get an in-depth understanding of applicants’ cognitive abilities, and reduce evaluation overheads.

TCS iON Certification on Artificial Intelligence demonstrate domain knowledge in AI and showcase AI developer skills to potential recruiters.  This helps both students and professionals to gain a job in top companies.

 

Objective of the program: To empower the students or professionals with the knowledge that helps them to grow as an AI researcher.

  • Duration: 180* Hours
  • For Students & Professionals
  • Instructor led sessions
  • Online access to OpenCV modules
  • Optional Advanced modules
  • 100 Free GPU hours of Azure credits to be used with Microsoft Azure Cloud Services
  • TCS iON certification exam on AI is included

 

Sources:
1.         Available at: https://www.sas.com/en_in/insights/analytics/what-is-artificial-intelligence.html.

Course Content


  1. Types of Data
  2. Data Collection or Data entry
  3. Data coding
  4. Data manipulation
  5. Creating tables and graphs
  6. Hypothesis testing (including designing a hypothesis statement)
  7. Reporting and publishing
  8. 5 data sets will be used in this session

Introduction to Data Science

  • Big Data
  • Characteristics of data
  • Hypothesis

Data Science Tools

  • Open Source
  • Commercial

Introduction to Python

  • Python Interpreter
  • Variables
  • Data types
  • Data Structures
  • Loops

Python crash course

  • Advanced Data Structures

  • Pandas

  • Numpy

Basics of Statistics

Data Collection

  • Types
  1. Structured
  2. Unstructured
  • Sources
  • Munging
  1. Cleaning
  2. Preprocessing

Data Visualization

  • Graphs

Data Analysis

  • Exploratory Data Analysis
  • Analytics
  1. Descriptive
  2. Diagnostics
  3. Prescriptive
  4. Predictive

Predictive Analytics

  1. Inferential Statistics
  2. Models
  3. OLS
  4. Regression
  • Linear
  • Logistic
  1. Decision Trees

Capstone Project – 10 hrs

Example Projects:

  1. Fake News Dataset
  2. Foreign Exchange Rates
  3. Netflix Movies

Introduction

Types of Learning

a) Supervised

b) Unsupervised

c) Semi Supervised

Machine Learning concepts

a) Generalization ability

b) Underfitting

c) Overfitting

d) Bias – Variance trade-off

e) Hyperparameters

f) Gradient Descent

Feature Engineering

a) Dimensionality Reduction

b) PCA

Types of prediction - Supervised

a) Regression

b) Classification

Regression

a) Linear

b) Polynomial

c) Logistic

Classification

1. Trees

(a) Decision Trees

(b) Ensembles

I Random Forests

Ii AdaBoost

2. Support Vectors

 

Model Validation techniques

a) Train – Test split

b) Cross Validation

c) K-fold

Clustering - Unsupervised

a) K-Means

b) K-NN

c) Spectral Clustering

d) Hierarchical Clustering

e) Agglomerative Clustering

 

Recommendation Systems

•Naïve
•Collaborative Filtering

NLP

•NLTK
•Sentiment Analysis

Model Deployment

Auto ML 

Capstone project – 10-15 hrs

 

Example Projects:

a) Recommendation Engine

b) Stock Price Prediction

c) Sentiment Analysis

Introduction

Theoretical background

a. Statistics

b. Linear Algebra

c. Probability Distributions

 

Concepts

a) Gradient Descent

b) Gradient propagation

c) Neurons

d) Activation Functions

e) Optimization Algorithms

f) Hyperparameters

Neural Networks introduction

1. Types of layers

a) Input

b) Hidden

c) Output

2. Types of networks

a) Shallow

b) Deep

3. Transfer learning

 

Convolutional Neural Networks (CNNs)

1. Types of operations

a) Strides

b) Padding

c) Convolutions

d) Pooling

 

OpenCV

1. Introduction to OpenCV

2.Images

•Basics
•Operations

3.Videos

•Basics
•Manipulations

4.Application of Deep Learning in OpenCV

•Face
•Recognition
•Alignment
•Landmark Detection
•Smile detection
•Morphing
•Aging 

5.Popular CNN Networks

•LeNet
•RetinaNet
•Faster RCNN

6.TorchVision

7.Segmentation

•UNet
•DeepLab
•SegNet
•LinkNet
•Fully Convolutional Network

8.Pose Estimation

•DensePose
•Squat

9.Object Detectors

•YOLO
•SSD
•Custom

Advanced Deep Learning

1.Recurrent Neural networks (RNNs)

2.Encoder/Decoder

3.Sequencers

4.GANs

 

Frameworks in Python

•Pytorch or Tensorflow

Advances in Deep Learning 

Capstone project – 15-20 hrs

 

To get TCS iON Certification:

  • Student will be provided with the TCS iON certification exam slot to complete the exam.  Student has to pass the exam to get TCS iON certification.

OpenCV:

  • Student gets Certificate of Completion

 

This module will open the students mind to the research opportunities existing worldwide and provide training on essential skills. Criteria – B.tech students with 60% are eligible All master degree holders with a 1st class marks are eligible.

  1. Writing a literature review
  2. Designing a Research Proposal
  3. Designing ethical approval documents
  4. Jurisprudence
  5. Speaking about your project
  6. How to apply for a research position?

Certificate

On completion, you can download and print off a certificate that is endorsed by the relevant professional body.

Download Certificate

Partners



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Highlights
  • Duration: 180* Hours
  • For Students & Professionals
  • Instructor led sessions
  • Online access to OpenCV modules
  • Optional Advanced modules
  • 100 Free GPU hours of Azure credits to be used with Microsoft Azure Cloud Services
  • TCS iON certification exam on AI is included