Download [UDEMY] DATA SCIENCE A-Z™: REAL-LIFE DATA SCIENCE EXERCISES INCLUDED torrent

[UDEMY] DATA SCIENCE A-Z™: REAL-LIFE DATA SCIENCE EXERCISES INCLUDED

Torrent:	[UDEMY] DATA SCIENCE A-Z™: REAL-LIFE DATA SCIENCE EXERCISES INCLUDED
Description:	What Will I Learn? Successfully perform all steps in a complex Data Science project Create Basic Tableau Visualisations Perform Data Mining in Tableau Understand how to apply the Chi-Squared statistical test Apply Ordinary Least Squares method to Create Linear Regressions Assess R-Squared for all types of models Assess the Adjusted R-Squared for all types of models Create a Simple Linear Regression (SLR) Create a Multiple Linear Regression (MLR) Create Dummy Variables Interpret coefficients of an MLR Read statistical software output for created models Use Backward Elimination, Forward Selection, and Bidirectional Elimination methods to create statistical models Create a Logistic Regression Intuitively understand a Logistic Regression Operate with False Positives and False Negatives and know the difference Read a Confusion Matrix Create a Robust Geodemographic Segmentation Model Transform independent variables for modelling purposes Derive new independent variables for modelling purposes Check for multicollinearity using VIF and the correlation matrix Understand the intuition of multicollinearity Apply the Cumulative Accuracy Profile (CAP) to assess models Build the CAP curve in Excel Use Training and Test data to build robust models Derive insights from the CAP curve Understand the Odds Ratio Derive business insights from the coefficients of a logistic regression Understand what model deterioration actually looks like Apply three levels of model maintenance to prevent model deterioration Install and navigate SQL Server Install and navigate Microsoft Visual Studio Shell Clean data and look for anomalies Use SQL Server Integration Services (SSIS) to upload data into a database Create Conditional Splits in SSIS Deal with Text Qualifier errors in RAW data Create Scripts in SQL Apply SQL to Data Science projects Create stored procedures in SQL Present Data Science projects to stakeholders Requirements Only a passion for success All software used in this course is either available for Free or as a Demo version Description Extremely Hands-On… Incredibly Practical… Unbelievably Real! This is not one of those fluffy classes where everything works out just the way it should and your training is smooth sailing. This course throws you into the deep end. In this course you WILL experience firsthand all of the PAIN a Data Scientist goes through on a daily basis. Corrupt data, anomalies, irregularities – you name it! This course will give you a full overview of the Data Science journey. Upon completing this course you will know: How to clean and prepare your data for analysis How to perform basic visualisation of your data How to model your data How to curve-fit your data And finally, how to present your findings and wow the audience This course will give you so much practical exercises that real world will seem like a piece of cake when you graduate this class. This course has homework exercises that are so thought provoking and challenging that you will want to cry… But you won’t give up! You will crush it. In this course you will develop a good understanding of the following tools: SQL SSIS Tableau Gretl This course has pre-planned pathways. Using these pathways you can navigate the course and combine sections into YOUR OWN journey that will get you the skills that YOU need. Or you can do the whole course and set yourself up for an incredible career in Data Science. The choice is yours. Join the class and start learning today! See you inside, Sincerely, Kirill Eremenko Who is the target audience? Anybody with an interest in Data Science Anybody who wants to improve their data mining skills Anybody who wants to improve their statistical modelling skills Anybody who wants to improve their data preparation skills Anybody who wants to improve their Data Science presentation skills Size: 8.54G Content retrieved from: udemy For more content visit: Free Tutorials
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Show Files »	[FreeTutorials.Us] datascience 01 Get Excited 001 Welcome to Data Science A-ZTM.mp4 (34.8 MB) 02 What is Data Science 002 Intro what you will learn in this section.mp4 (7.7 MB) 003 Profession of the future.mp4 (26.9 MB) 004 Areas of Data Science.mp4 (19.2 MB) 005 IMPORTANT Course Pathways.mp4 (18.6 MB) 006 BONUS Success Story.html (1.8 KB) 03 --------------------------- Part 1 Visualisation --------------------------- 007 Welcome to Part 1.mp4 (30.4 MB) 04 Introduction to Tableau 008 Intro what you will learn in this section.mp4 (13.3 MB) 009 Installing Tableau Desktop and Tableau Public FREE.mp4 (41.9 MB) 010 Challenge description view data in file.mp4 (21.2 MB) 011 Connecting Tableau to a Data file - CSV file.mp4 (24.9 MB) 012 Navigating Tableau - Measures and Dimensions.mp4 (25.1 MB) 013 Creating a calculated field.mp4 (23.3 MB) 014 Adding colours.mp4 (25.9 MB) 015 Adding labels and formatting.mp4 (41.7 MB) 016 Exporting your worksheet.mp4 (37.4 MB) 017 Section Recap.mp4 (5.6 MB) quizzes 001 Tableau Basics.html (4.6 KB) 05 How to use Tableau for Data Mining 018 Intro what you will learn in this section.mp4 (13.3 MB) 019 Get the Dataset Project Overview.mp4 (24.1 MB) 020 Connecting Tableau to an Excel File.mp4 (19.8 MB) 021 How to visualise an ad-hoc A-B test in Tableau.mp4 (19.8 MB) 022 Working with Aliases.mp4 (16.4 MB) 023 Adding a Reference Line.mp4 (21.9 MB) 024 Looking for anomalies.mp4 (34.4 MB) 025 Handy trick to validate your approach data.mp4 (37.3 MB) 026 Section Recap.mp4 (16.2 MB) 06 Advanced Data Mining With Tableau 027 Intro what you will learn in this section.mp4 (15.2 MB) 028 Creating bins Visualizing distributions.mp4 (44.2 MB) 029 Creating a classification test for a numeric variable.mp4 (20.8 MB) 030 Combining two charts and working with them in Tableau.mp4 (26.9 MB) 031 Validating Tableau Data Mining with a Chi-Squared test.mp4 (50.5 MB) 032 Chi-Squared test when there is more than 2 categories.mp4 (21.3 MB) 033 Visualising Balance and Estimated Salary distribution.mp4 (71.1 MB) 034 Bonus Chi-Squared Test Stats Tutorial.mp4 (75.0 MB) 035 Bonus Chi-Squared Test Part 2 Stats Tutorial.mp4 (39.6 MB) 036 Section Recap.mp4 (19.7 MB) 037 Part Completed.mp4 (2.2 MB) 07 --------------------------- Part 2 Modelling --------------------------- 038 Welcome to Part 2.mp4 (50.4 MB) 08 Stats Refresher 039 Intro what you will learn in this section.mp4 (7.2 MB) 040 Types of variables Categorical vs Numeric.mp4 (13.0 MB) 041 Types of regressions.mp4 (10.3 MB) 042 Ordinary Least Squares.mp4 (5.1 MB) 043 R-squared.mp4 (7.9 MB) 044 Adjusted R-squared.mp4 (16.4 MB) 09 Simple Linear Regression 045 Intro what you will learn in this section.mp4 (12.7 MB) 046 Introduction to Gretl.mp4 (22.9 MB) 047 Get the dataset.mp4 (18.6 MB) 048 Import data and run descriptive statistics.mp4 (14.4 MB) 049 Reading Linear Regression Output.mp4 (29.7 MB) 050 Plotting and analysing the graph.mp4 (31.0 MB) 10 Multiple Linear Regression 051 Intro what you will learn in this section.mp4 (26.8 MB) 052 Caveat assumptions of a linear regression.mp4 (4.3 MB) 053 Get the dataset.mp4 (35.9 MB) 054 Dummy Variables.mp4 (41.5 MB) 055 Dummy Variable Trap.mp4 (12.5 MB) 056 Ways to build a model BACKWARD FORWARD STEPWISE.mp4 (25.7 MB) 057 Backward Elimination - Practice time.mp4 (95.2 MB) 058 Using Adjusted R-squared to create Robust models.mp4 (95.7 MB) 059 Interpreting coefficients of MLR.mp4 (88.9 MB) 060 Section Recap.mp4 (16.5 MB) 11 Logistic Regression 061 Intro what you will learn in this section.mp4 (37.2 MB) 062 Get the dataset.mp4 (9.0 MB) 063 Binary outcome YesNo-Type Business Problems.mp4 (36.2 MB) 064 Logistic regression intuition.mp4 (43.0 MB) 065 Your first logistic regression.mp4 (41.7 MB) 066 False Positives and False Negatives.mp4 (22.9 MB) 067 Confusion Matrix.mp4 (11.0 MB) 068 Interpreting coefficients of a logistic regression.mp4 (50.7 MB) 12 Building a robust geodemographic segmentation model 069 Intro what you will learn in this section.mp4 (15.3 MB) 070 Get the dataset.mp4 (27.1 MB) 071 What is geo-demographic segmenation.mp4 (15.8 MB) 072 Lets build the model - first iteration.mp4 (34.4 MB) 073 Lets build the model - backward elimination STEP-BY-STEP.mp4 (97.4 MB) 074 Transforming independent variables.mp4 (52.4 MB) 075 Creating derived variables.mp4 (41.8 MB) 076 Checking for multicollinearity using VIF.mp4 (86.8 MB) 077 Correlation Matrix and Multicollinearity Intuition.mp4 (48.8 MB) 078 Model is Ready and Section Recap.mp4 (35.0 MB) 13 Assessing your model 079 Intro what you will learn in this section.mp4 (8.9 MB) 080 Accuracy paradox.mp4 (6.0 MB) 081 Cumulative Accuracy Profile CAP.mp4 (27.4 MB) 082 How to build a CAP curve in Excel.mp4 (127.0 MB) 083 Assessing your model using the CAP curve.mp4 (28.5 MB) 084 Get my CAP curve template.mp4 (44.9 MB) 085 How to use test data to prevent overfitting your model.mp4 (13.8 MB) 086 Applying the model to test data.mp4 (88.6 MB) 087 Comparing training performance and test performance.mp4 (87.3 MB) 088 Section Recap.mp4 (12.6 MB) 14 Drawing insights from your model 089 Intro what you will learn in this section.mp4 (8.3 MB) 090 Power insights from your CAP.mp4 (85.6 MB) files
Added:	2017-10-23 17:21:04
Language:	English
Peers:	Seeders : 16 , Leechers : 9
Tags:	UDEMY DATA SCIENCE TUTORIALS
Release name:	[UDEMY] DATA SCIENCE A-Z™: REAL-LIFE DATA SCIENCE EXERCISES INCLUDED
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