Curriculum Ideology

Program Overview

This course is designed for Working Professionals & Graduates who have no previous knowledge of Data Analytics & Data Science but wish to acquire these skills in a short period of time. These students will learn how to Analyze large data sets aidentify patterns, along with data science, Machine Learning & AI algorithims that will improve any company’s and organization decision-making process. After completing the course, they will be able to: -Undertake data collection, preprocessing and analysis -Building models to address business problems -Presenting information using data visualization techniques -Build predictive models and machine-learning algorithms -Combine models through ensemble modeling -Propose solutions and strategies to business challenges – Capture, categorize, simplify, normalize and prepare data to be processed – Visually represent analysis’s conclusions to technical and non technical audiences – Use the most common algorithms, to make sense of large amounts of data, which are applicable to most business and management problems. At the end of the program, you will have a professional portfolio of projects and real experience with data analysis that will give you the necessary confidence to be successful as a Data Analyst.

Internship

As competition for graduate jobs increases, students need to think of new ways to set themselves apart from all of the other equally qualified and skilled candidates. Graduates who have relevant workplace experience tend to be more valued by employers, and this makes internships an attractive prospect. give you practical skills, workplace experience and greater knowledge of that industry, in exchange for the employer benefiting from your labour.

Course Objectives

The main goal of this course is to help students learn, understand, and practice big data analytics and machine learning approaches, which include the study of modern computing big data technologies and scaling up machine learning techniques focusing on industry applications. Almost every company and organization collects data about their operations to better understand how to make internal improvements. As the amount of data collected increases, it is more difficult to analyze this data manually. There is a growing tendency at bigger companies to automate the collection of large quantities of data (Big Data) to discover behavior patterns and better understand their internal processes.

Course Pre-requisites

Those interested in Data Scientists should have some prior experience in (or be willing to work with):

Basic Mathematics
Programming Language like Python,R(or willing to learn)
Statistics (working with numbers and statistical methodology)
This course is well suited to those with a degree in Social and natural Sciences,Engineering, Mathematics,Art & other and Also for domain knowledge experts(Working Professional).

Course Grading

Grades will be determined from:

Attendance (40%) Programming exercises and deliverables at the end of every task (40%) and final presentation (20%) Evaluation scheme is subject to change with a prior notice. Attendance will be checked regularly. Missing classes frequently will automatically drop student out of class.

Programme methodology

This programme is based on Smart Practical Methodology (SPM). This involves advanced simulation techniques of real situations. There are no theoretical classes or rote learning study sessions to pass exams. SPM puts you in a motivating scenario based on a real professional situation in which you perform the same tasks as actual professionals, using the same tools, meaning that you can fit easily into a real work team when the time comes. You will be working in a team, as is usually the case in the world of work. A comprehensive range of supporting material and the help needed to complete the tasks are available on-line. You will be supervised by a tutor, who is always available to answer any questions or clear up any doubts, and who will assess your performance and advise on the project “deliverables”. SPM is an educational methodology that enables us to offer a learning-by-doing approach in all its complexity and scope. This methodology has been successfully used for more than 10 years at different Universities & Institutions in US & UK, where many students have completed programmes developed using this methodology.

Tutors

At the start of the course you are assigned a tutor who is a professional expert. The tutor will foster teamwork and promote discussion of issues, helping you find solutions and resolve the difficulties of the project by drawing on your own resources. They will give you feedback on the “deliverables” for each project at every stage, so that you can continually refine them, learning from your mistakes and achieving the mastery needed for each task.

Course Highlights

Curriculum

Talent Shiksha’s program curriculum is designed in a way to cover all the execution related Data Science SKills & managerial skills. The vision is to impart learning in a practical manner and provide our students with industry best exposure. Here are the core concepts that you will be learning:

Batch Schedule

Why Talent Shiksha is Industry Best?