Data Science A-Z™: Real-Life Data Science Exercises Included 2019-6

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Description

Description

Data Science AZ: Real-Life Data Science Exercises Included is the name of a course on Udemy that introduces you to step-by-step data science and provides examples in statistics and data analysis, modeling, And teaches you a visualization of data. Data science is the knowledge that begins by extracting knowledge from a set of data and information using scientific systems, algorithms, and methods. In this course, you will become familiar with data science and learn the essentials of becoming an information scientist.

During this course, you will learn how to clean up your data and prepare it for analysis. You will then learn how to visualize and model information. In the following, you will learn about the process of fitting the data curve and finally learn how to prepare your results for presentation. This course provides you with many hands-on exercises and prepares you to meet real-world challenges. The tutor will also teach you how to work with tools like SQL, SSIS, Tableau, and Gretl.

Courses taught in this course


  • Perform all the steps in a complex data science project
  • Create a basic Tableau visualization
  • Data Extraction in Tableau
  • Learn how to apply Pearson’s statistical test
  • Implementation of ordinary least squares method for constructing linear regression
  • R-Squared evaluation for a variety of models
  • Build SLR and MLR
  • Making a logical regression
  • Read a jumble matrix
  • Creating a CAP Curve in Excel
  • Understand the odds ratio
  • Creating Scripts in SQL
  • Creating conditional parts in SSIS

Data Science A-Z: Real-Life Data Science Exercises Included

  • English language
  • Duration: 21:09:24
  • Number of courses: 213
  • Level of education: Intermediate
  • Teacher: Kirill Eremenko ، SuperDataScience Team
  • File format: mp4

Course headings

Course content
213 lectures 21:09:24

Get Excited
2 lectures 05:43

What is Data Science?
6 lectures 22:45

——— Part 1: Visualization ———
1 reading 01:57

Introduction to Table
10 Readings 59:12

How to use Tableau for Data Mining
9 lectures 50:11

Advanced-Data Mining With Tableau
11 lectures 01:29:07

————————— Part 2: Modelling —————————
1 lecture 03:54

Stats Refresher
6 lectures 32:22

Simple Linear Regression
6 lectures 22:49

Multiple Linear Regression
10 lectures 01:16:37

Logistic Regression
8 lectures 01:03:04

Building a robust geodemographic segmentation model
10 lectures 01:12:31

Assessing your model
10 lectures 01:09:11

Drawing insights from your model
7 lectures 50:31

Model maintenance
5 lectures 30:38

————————— Part 3: Data Preparation —————————
1 lecture 02:24

Business Intelligence (BI) Tools
8 lectures 33:24

ETL Phase 1: Data Wrangling before the Load
6 lectures 11:42

ETL Phase 2: Step-by-step guide to uploading data using SSIS
7 lectures 23:01

Handling errors during ETL (Phases 1 & 2)
16 lectures 02:09:26

SQL Programming for Data Science
17 lectures 01:12:09

ETL Phase 3: Data Wrangling after the load
16 lectures 01:44:20

Handling errors during ETL (Phase 3)
12 lectures 01:09:44

————————— Part 4: Communication —————————
1 lecture 01:31

Working with people
8 lectures 29:05

Presenting for Data Scientists
11 lectures 01:02:54

Homework Solutions
7 lectures 01:16:57

Bonus readings
1 reading 02:13

Course prerequisites


  • Only a passion for success
  • All software used in this course is either available for Free or as a Demo version

Pictures

Real-Life Data Science Exercises Included

Real-Life Data Science Exercises Included

Sample video

[su_vimeo url=”https://vimeo.com/362554107″ width=”600″ height=”400″]

Installation guide

View with your favorite Player after Extract.

English subtitle

Quality: 720p

Download

[su_table style=”default”]

File Name Size Link Backup link
Chapter 1 – 14 1.24 GB Download Download
Chapter 15 – 21 1.14 GB Download Download
Chapter 22 – 25 860 MB Download Download
Chapter 26 – 28 798 MB Download Download

[/su_table]

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