Udemy

Intro to Data Science Using Python: Your Best Starting Point

Enroll Now
  • 287 Students
  • Updated 2/2020
  • Certificate Available
4.6
(27 Ratings)
CTgoodjobs selects quality courses to enhance professionals' competitiveness. By purchasing courses through links on our site, we may receive an affiliate commission.

Course Information

Registration period
Year-round Recruitment
Course Level
Study Mode
Duration
1 Hour(s) 46 Minute(s)
Language
English
Taught by
‫Ali Desoki
Certificate
  • Available
  • *The delivery and distribution of the certificate are subject to the policies and arrangements of the course provider.
Rating
4.6
(27 Ratings)
1 views

Course Overview

Intro to Data Science Using Python: Your Best Starting Point

Learn About Data Science And Machine Learning Using Python To Start Your Career In Those Fields. The Best Starting Point

Welcome to “Introduction to Data Science Using Python” where you will set a good foot in the fields of Data Science and Machine Learning.

I'm your instructor Ali Desoki and I start from scratch going clearly over all the points in the course along with hands-on practical exercises and projects to summarize all the skills you’ve learned.

This course is designed for Beginners covering all Aspects of what you need to know to start in the fields of data science and machine learning with practice notebooks which summarize all the skills you’ve learned.

At the end of this course, you will be able to analyze and manipulate data with python and be able to start your career in this field.

This course covers a lot of useful and essential topics including:

Introduction to Data Science

Data Science Most Used Packages

Data Wrangling

Model Development

Model Refinement

Model Evaluation Techniques and more...

The ideal student for this course is someone who looks to start in the mentioned fields from scratch.

All you need to know is Python and basic statistics to start this course.

So what are you waiting for! Enroll now and jump-start your career in Data Science and Machine Learning.

Course Content

  • 6 section(s)
  • 29 lecture(s)
  • Section 1 Pre Introduction: Installation and Guides
  • Section 2 Review Introduction
  • Section 3 Data Wrangling
  • Section 4 Exploratory Data Analysis
  • Section 5 Model Development
  • Section 6 Model Evaluation and Refinement

What You’ll Learn

  • Introduction to Data Science
  • Data Science Most Used Packages
  • Data Wrangling
  • Model Development
  • Model Refinement
  • Model Evaluation Techniques

Reviews

  • R
    Repula Manhattan
    5.0

    Very clear explanations and amazing labs sections

  • J
    Jasmin Elliot
    5.0

    I enjoyed this free learning experience, thanks for the coupon

  • P
    Parcel Gonzalez
    5.0

    After completing the course, I can sat it is exactly as described, easy and fun

  • G
    Gilbert Andrew
    5.0

    Nice course, well experienced instructor. High video quality. really recommend

Start FollowingSee all

We use cookies to enhance your experience on our website. Please read and confirm your agreement to our Privacy Policy and Terms and Conditions before continue to browse our website.

Read and Agreed