Certificate Program in Data Science using Python

Learn concepts of data science using Python with hands-on case studies

paid 0(0 Ratings) 1 Students Enrolled
Created By Imurgence i Last Updated Mon, 11-Feb-2019
+ View More
Description
This Imurgence course covers topics including basic statistics and linear and logistic regression.

  • Upon successful completion of this course, the learner will be skilled in Python programming to perform data analytics on business data and apply data science concepts on data. This will give the learner ability to do predictive modelling using Linear Regression and Logistic Regression.

Target Audience
This course is ideal for anyone looking to improve their skills or start a career in data science, business analytics, artificial intelligence (AI) or machine learning.

Access Time frame
Six months from the date of access.

Prerequisites
The prerequisites for this course would include Python Programming. As a recommendation the learner is advised to complete the Certificate Program in Data Analytics using Python before taking up this course.

Type of Certification
Certificate of Completion

Format of Certification
Digital

Professional Association/Affiliation
The certificate is issued by Imurgence an autonomous institution and endorsed by SiCureMi an IIT Delhi incubated Analytics Firm.

Method of Obtaining Certification
Upon successful completion of this course, the learner will be sent a digital copy of the certificate to their email.



Curriculum For This Course
65 Lessons 07:50:46 Hours
Basic Statistics
15 Lessons 01:03:51 Hours
  • Introduction To Statistics 1.1 00:01:22
  • Introduction to Statistics 1.2 00:03:44
  • Introduction to Statistics 1.3 00:06:20
  • Introduction To Statistics 1.4 00:04:54
  • Introduction To Statistics 1.5 00:03:51
  • Introduction To Statistics 1.6 00:06:10
  • Introduction To Statistics 1.7 00:07:11
  • Introduction To Statistics 1.8 00:05:11
  • Introduction To Statistics 1.9 00:02:11
  • Introduction To Statistics 1.10 00:00:58
  • Introduction To Statistics 1.11 00:04:38
  • Introduction To Statistics 1.12 00:02:26
  • Introduction To Statistics 1.13 00:04:42
  • Introduction To Statistics 1.14 00:05:51
  • Introduction To Statistics 1.15 00:04:22
  • Linear Regression 2.1 00:05:01
  • Linear Regression 2.2 00:03:27
  • Linear Regression 2.3 00:02:42
  • Linear Regression 2.4 00:04:56
  • Linear Regression 2.5 00:08:09
  • Linear Regression 2.6 00:01:56
  • Linear Regression 2.7 00:03:04
  • Linear Regression 2.8 00:02:39
  • Linear Regression 2.9 00:06:42
  • Linear Regression 2.10 00:05:45
  • Linear Regression 2.11 00:04:32
  • Linear Regression 2.12 00:08:20
  • Linear Regression 2.13 00:04:50
  • Simple Linear Regression 2.14 00:11:20
  • Simple Linear Regression 2.15 00:04:58
  • Simple Linear Regression 2.16 00:06:17
  • Simple Linear Regression 2.17 00:09:17
  • Multiple Linear Regression 2.18 00:15:45
  • Multiple Linear Regression 2.19 00:06:32
  • Multiple Linear Regression 2.20 00:06:45
  • Multiple Linear Regression 2.21 00:08:29
  • Multiple Linear Regression 2.22 00:02:50
  • Multiple Linear Regression 2.23 00:05:00
  • Multiple Linear Regression 2.24 00:08:18
  • Multiple Linear Regression on Boston Dataset 2.25 00:12:58
  • Multiple Linear Regression on Boston Dataset 2.26 00:13:06
  • Multiple Linear Regression on Boston Dataset 2.27 00:09:14
  • Multiple Linear Regression on Boston Dataset 2.28 00:09:51
  • Multiple Linear Regression on Boston Dataset 2.29 00:08:35
  • Multiple Linear Regression on Boston Dataset 2.30 00:19:18
  • Multiple Linear Regression on Boston Dataset 2.31 00:12:12
  • Logistic Regression 3.1 00:04:51
  • Logistic Regression 3.2 00:06:53
  • Logistic Regression 3.3 00:03:46
  • Logistic Regression 3.4 00:10:58
  • Logistic Regression 3.5 00:10:01
  • Logistic Regression 3.6 00:04:47
  • Logistic Regression 3.7 00:07:58
  • Logistic Regression 3.8 00:04:22
  • Logistic Regression 3.9 00:06:29
  • Logistic Regression 3.10 00:12:29
  • Logistic Regression 3.11 00:10:54
  • Logistic Regression 3.12 00:14:13
  • Logistic Regression on Diabetes Dataset 3.13 00:11:11
  • Logistic Regression on Diabetes Dataset 3.14 00:12:30
  • Logistic Regression on Diabetes Dataset 3.15 00:07:49
  • Logistic Regression on Diabetes Dataset 3.16 00:07:08
  • Logistic Regression on Diabetes Dataset 3.17 00:16:16
  • Logistic Regression on Diabetes Dataset 3.18 00:07:29
  • Logistic Regression on Diabetes Dataset 3.19 00:14:03
+ View More
Other Related Courses
About The Instructor
  • 1 Reviews
  • 62 Students
  • 18 Courses
+ View More
A Data Science Training Company
Powered by Simple & Real Analytics
Student Feedback
0
Average Rating
  • 0%
  • 0%
  • 0%
  • 0%
  • 0%
Reviews
2000
Buy Now
Includes:
  • Self-Paced Training
  • 07:50:46 Hours Videos
  • 65 Lessons
  • Certification Course
  • All Levels