#Job skill
Data Science Foundation Course
- Knowledge-packed, project-based intensive course
- Hands-on practice & live-online learning from the comfort of your home
- Training and Mentoring from industry experts and super supportive TAs
- A Certificate on successful completion of the course
Pick up Data Science by actually getting your hands dirty!
Wondering whether you should go through all the trouble? Take this Bootcamp if -
- You are looking forward to start your data science career
- You're on the fence on whether data science is the right choice
- You want to see data science in action and talk to industry experts
- You simply want to take up a data science project
Ready for a Data Science Career?
Year after year, the one profession that consistently ranks on top amongst emerging jobs is Data Science. Growing exponentially at more than 25% every year, Data Science finds increasing use in more and more industries by the day, with exciting applications such as self-driving cars, intelligent automation, and dynamic business decision support systems to show for. This is a growing profession whose demand in every industry and sector is increasing by the day.
Data Science is without a shadow of doubt, a bright and promising career choice
Program Curriculum
Designed by our trainers who come with years of industry experience, this bootcamp is a blend of both up-to-date theory and relevant practical application. Broadly, the topics we’ll cover in this program include:
- Data Science in the Real World
- Introduction to Logistic Regression
- Introduction to the Project
- Exploratory Data Analysis
- Applying the ML Algorithm
- Visualizing the Model
Project Overview: Predict the Absenteeism of an Employee
The goal of the project is to predict the probability of an employee being absent on the basis of various metrics (health issues, personal issues, whereabouts, work load).
For this project, we shall use Python to understand the key steps in the Data Science process such as data cleaning, data exploration, and data visualization. We shall then implement an appropriate Machine Learning algorithm and gain deeper insights in the given dataset.
