Note: Course Fee of Rs 6500

Course on Python Programming and Machine Learning

Course Description

Today python has a great demand in the industry. So if you learn this language it will help you to get your dream job also! Python is a very easy to learn and powerful language. The size of the code is too small. If you want to build a simple Java or C program of Hello World it will take 6/7 line But in python it is just print "hello world!". Machine Learning with Python course dives into the basics of Machine Learning using Python, an approachable and well-known programming language. You'll learn about Supervised vs Unsupervised Learning, look into how Statistical Modeling relates to Machine Learning, and do a comparison of each. Look at real-life examples of Machine Learning and how it affects society in ways you may not have guessed!
Overview
• Python setup
• Python IDE
• Variables
• Python Operators
• Arithmetic Operator
• Comparison Operator
• Assignment Operator
• Bitwise Operator
• Membership Operator
• Identity Operator
• If Statement
• If Else Statement
• Break & Continue Statement
• For Loop
• While Loop
• String
• Number
• List
• Dictionary
• Function
• Module
• Exception
• File Operation
• File Reading
• File Writing
• Appending File
• Numerical Analysis and Data Exploration with NumPy Arrays, and Data Visualization with Matplotlib - Accessing, Preparing, and Exploring Data with Pandas
- ML Projects

INTRODUCTION TO MACHINE LEARNING
Course Description

Machine learning uses interdisciplinary techniques such as statistics, linear algebra, optimization, and computer science to create automated systems that can sift through large volumes of data at high speed to make predictions or decisions without human intervention. Machine learning as a field is now incredibly pervasive, with applications spanning from business intelligence to homeland security, from analyzing biochemical interactions to structural monitoring of aging bridges, and from emissions to astrophysics, etc. This class will familiarize students with a broad cross-section of models and algorithms for machine learning, and prepare students for research or industry application of machine learning techniques.

Overview

Based on fundamental knowledge of computer science principles and skills, probability and statistics theory, and the theory and application of linear algebra. This course provides a broad introduction to machine learning and statistical pattern recognition.
Topics include:
1. Supervised learning (generative/discriminative learning, parametric/non- parametric learning, neural networks, and support vector machines) – 2.
Unsupervised learning (clustering, dimensionality reduction, kernel methods) –
3. Learning theory (bias/variance tradeoffs; VC theory; large margins);
4. Reinforcement learning and adaptive control.

Duration: 2 weeks alternate days

Course Fee: Rs. 3000/-

Course on R Programming

Course Description • Overview
• Environment Setup
• Basic Syntax
• Data Types
• Variables
• Operators
• Decision Making
• Loops
• Functions
• Strings
• Vectors
• List
• Matrices
• Arrays
• Factors
• Data Frames
• Packages
• Data Reshaping
• Data Interfaces
• Charts & Graphs
• Statistics Example

Duration: 2 weeks alternate days
Course Fee: Rs. 3000/-

Course on Cloud Computing

Course Description

Introduction to Cloud Computing.
Cloud Service Models.
Cloud Deployment Models.
Resource Management in Cloud
Cloud Computing - Management
Cloud Computing - Data Storage
Cloud Computing - Virtualization
Cloud Computing - Security
Cloud Computing - Operation
Cloud Computing - Applications
Cloud Computing - Providers
Cloud Computing - Challenges
Mobile Cloud Computing
Introduction to Ubuntu and its commands
Implementation of private cloud & Open Source software and Commercial Clouds

Duration: 2 weeks alternate days
Course Fee: Rs. 3000/-

Registration for the above courses starts from 3rd May 2021. For Admission, kindly fill the registration form:
Registration Form Link: Click Here