Offered By in collaboration with

Click here to integrate the TCS iON Industry Honour Course with your academic program

Course Details

Course Commencement
August 2023 (Tentative)
Course Completion
January 2024 (Tentative)
Language
English
Exam Dates
Multiple slots in January 2024 (Tentative)
Credits & LTP
Each course offers 5 credit points.
Lecture
3
Tutorial
1
Practical (Hands-on)
1
Credit
5
Recommended For:
Graduation Programme - B.E./B.Tech
Branch - Computer Science Engineering and Information Technology, Electronics and Communication Engineering, Mechanical Engineering
Semester -
5 th,  6 th,  7 th  and  8 th

Course Summary

Data analysis is the need of the hour. Data is nowadays considered as a fuel to develop different machine learning/statistical algorithms. According to Grand View Research, the global data analytics outsourcing market size was valued at US$2,006 million in 2017 and is expected to grow at a Compound Annual Growth Rate (CAGR) exceeding 22.8% from 2018 to 2025.

The Data Analytics and Reporting course provides students with an introduction to data, the various steps involved in data preprocessing, and the tools used to analyse data. The course has two important objectives: (1) the use of tools and techniques to analyse data properties; (2) to extract relevant information from data and use different ways of reporting data. Data analysis is the cornerstone for any predictive analytics wherein the steps involved in getting clean model development data consume almost 90% of the entire project effort. This course helps students to derive insights from the data based on machine learning models and create reports.

Hands-On

A virtual hands-on environment is integrated within the course.

Students will have to leverage this environment to complete the industry assignment as well as to complete the Part B section of the summative assessment.

+ Read More - Read Less
RECOMMENDED PRIOR KNOWLEDGE
1. Basic knowledge of programming and Data Structures Algorithms

2. Basic knowledge of Mathematics and Statistics

Course Syllabus

The course syllabus will be delivered through a combination of eLearning resources, digital lectures, community based digital classrooms as applicable.
+ Expand All - Collapse All
View More View Less
RELATED COURSES
+ More - Less

Course Components

Digital Learning
Resources
Courses to consist of enriching eLearning resources View Sample
Digital
Lectures
Multiple digital lectures delivered by a renowned academician and an industry expert, through the entire duration of a course View Sample
Academic Connect
Community
Moderated by an academic expert with a focus on building conceptual clarity View Sample
Industry Connect
Community
Moderated by an industry expert with a focus on building industry oriented applied knowledge View Sample
Industry
Assignment
Access to industry related mini projects to enable practical exposure for candidates View Sample
Practice
Assessment
Access to two practice assessments for self-evaluation View                         Sample
Summative Assessment
/TCS NQT
Candidates to appear for either summative assessments consisting of two parts - Test of Knowledge and Test of Application or TCS NQT View Sample
Verifiable Digital
Certificate
Successful candidates to receive a digital certificate, verifiable through online platforms View Sample
Internship
Opportunity
Internship opportunity for toppers in the respective courses, subject to vacancies in corporates and their hiring policies View Sample
Job
Visibility
Get visibility to job vacancies with leading corporate recruiters that recognise the TCS NQT certification, subject to vacancies in corporates and their hiring policies View Sample

Testimonials

!~Testimonials~!