Data Science Skillpath: SQL, ML, Looker Studio & Alteryx

سرفصل های دوره

[4-in-1 Bundle] Covers SQL, Data viz using Google's Looker Studio, Machine Learning using Python and ETL using Alteryx

1. Introduction

1. Introduction

2. Installation and getting started

1. Installing PostgreSQL and pgAdmin in your PC

2. This is a milestone!

3. If pgAdmin is not opening....html

4. Course Resources.html

3. Case Study Demo

1. Case Study Part 1 - Business problems

2. Case Study Part 2 - How SQL is Used

4. Fundamental SQL statements

1. CREATE

2. INSERT

3. Import data from File

4. SELECT statement

5. SELECT DISTINCT

6. WHERE

7. Logical Operators

8. UPDATE

9. DELETE

10. ALTER - Part 1

11. ALTER - Part 2

5. Restore and Back-up

1. Restore and Back-up

2. Debugging restoration issues

3. Creating DB using CSV files

4.1 Customer.csv

4.2 Product.csv

4.3 Sales.csv

4. Debugging summary and Code for CSV files.html

6. Selection commands Filtering

1. IN

2. BETWEEN

3. LIKE

7. Selection commands Ordering

1. Side Lecture Commenting in SQL

2. ORDER BY

3. LIMIT

8. Alias

1. AS

9. Aggregate Commands

1. COUNT

2. SUM

3. AVERAGE

4. MIN And MAX

10. Group By Commands

1. GROUP BY

2. HAVING

11. Conditional Statement

1. CASE WHEN

12. JOINS

1. Introduction to Joins

2. Concepts of Joining and Combining Data

3. Preparing the data

4. Inner Join

5. Left Join

6. Right Join

7. Full Outer Join

8. Cross Join

9. Intersect and Intersect ALL

10. Except

11. Union

13. Subqueries

1. Subquery in WHERE clause

2. Subquery in FROM clause

3. Subquery in SELECT clause

14. Views and Indexes

1. VIEWS

2. INDEX

15. String Functions

1. LENGTH

2. UPPER LOWER

3. REPLACE

4. TRIM, LTRIM, RTRIM

5. CONCATENATION

6. SUBSTRING

7. LIST AGGREGATION

16. Mathematical Functions

1. CEIL And FLOOR

2. RANDOM

3. SETSEED

4. ROUND

5. POWER

17. Date-Time Functions

1. CURRENT DATE And TIME

2. AGE

3. EXTRACT

18. PATTERN (STRING) MATCHING

1. PATTERN MATCHING BASICS

2. ADVANCE PATTERN MATCHING - Part 1

3. ADVANCE PATTERN MATCHING - Part 2

19. Window Functions

1. Introduction to Window functions

2. Introduction to Row number

3. Implementing Row number in SQL

4. RANK and DENSERANK

5. NTILE function

6. AVERAGE function

7. COUNT

8. SUM TOTAL

9. RUNNING TOTAL

10. LAG and LEAD

20. COALESCE function

1. COALESCE function

21. Data Type conversion functions

1. Converting Numbers Date to String

2. Converting String to Numbers Date

22. User Access Control Functions

1. User Access Control - Part 1

2. User Access Control - Part 2

23. Nail that Interview!

1. Tablespace

2. PRIMARY KEY And FOREIGN KEY

3. ACID compliance

4. Truncate

24. Looker Studio

1. Introduction

2. Why Data Studio

25. Terminologies And Theoretical concepts for Data Studio

1. Data Studio Home Screen And Dataset vs Data Source

2. Structure of Input data

3. Dimensions vs Measures (new definition)

26. Practical part begins here

1. Opening Data Studio and preparing data

2. Adding a data source

3. Managing added data source

27. Charts to highlight numbers

1. Data Table

2. Styling tab for data table

3. Scorecards

28. Charts for comparing categories Bar charts and stacked charts

1. Simple Bar and Column chart

2. Stacked Column chart

29. Charting maps of a country, continent or a region - Geomaps

1. GeoMap

30. Charts to highlight trends Time series, Line and Area charts

1. Time Series

2. Update to Time Series chart

3. Line Chart and Combo Chart

31. Highlight contribution to total Pie chart And Donut Chart

1. Pie Chart and Donut Chart

2. Stacked Area Charts

3.1 Areachart updated.csv

3. Updated data for area charts.html

32. Relationship between two or more variables Scatterplots

1. Scatter Plots and Bubble charts

33. Aggregating on two dimensions Pivot tables

1. Pivot tables for cross tabulation

34. All about a single Metric Bullet Chart

1. Bullet Chart

35. Chart for highlighting heirarchy TreeMap

1. TreeMaps

36. Branding a Report

1. Branding a Report Brand Logo and Company Details

2. Brand colors for report branding

37. Giving the power to filter Data to viewers

1. Filter controls for viewers

38. Add Videos, Feedback form etc. to your Report

1. URL Embed to include external content

39. Sometimes data is in multiple tables

1. Blending data from multiple tables

2. Different types of Joins while blending data

40. Sharing and collaborating on Data Studio report

1. Downloading report as PDF and Page Management

2. Sharing report and Data Credentials

3. Sharing report using a link

4. Scheduling emails

5. Embeding report on Website

41. Charting Best Practices

1. Highlighting chart message

2. Eliminating Distractions from the Graph

3. Avoiding clutter

4. Avoiding the Spaghetti plot

42. Machine Learning in Python

1. Introduction

43. Setting up Python and Jupyter notebook

1. Installing Python and Anaconda

2. Opening Jupyter Notebook

3. Introduction to Jupyter

4. Arithmetic operators in Python Python Basics

5. Strings in Python Python Basics

6. Lists, Tuples and Directories Python Basics

7. Working with Numpy Library of Python

8. Working with Pandas Library of Python

9. Working with Seaborn Library of Python

44. Basics of statistics

1. Types of Data

2. Types of Statistics

3. Describing data Graphically

4. Measures of Centers

5. Measures of Dispersion

45. Introduction to Machine Learning

1. Introduction to Machine Learning

2. Building a Machine Learning Model

46. Data Preprocessing

1. Gathering Business Knowledge

2. Data Exploration

3. The Dataset and the Data Dictionary

4. Importing Data in Python

5. Univariate analysis and EDD

6. EDD in Python

7. Outlier Treatment

8. Outlier Treatment in Python

9. Missing Value Imputation

10. Missing Value Imputation in Python

11. Seasonality in Data

12. Bi-variate analysis and Variable transformation

13. Variable transformation and deletion in Python

14. Non-usable variables

15. Dummy variable creation Handling qualitative data

16. Dummy variable creation in Python

17. Correlation Analysis

18. Correlation Analysis in Python

47. Linear Regression

1. The Problem Statement

2. Basic Equations and Ordinary Least Squares (OLS) method

3. Assessing accuracy of predicted coefficients

4. Assessing Model Accuracy RSE and R squared

5. Simple Linear Regression in Python

6. Multiple Linear Regression

7. The F - statistic

8. Interpreting results of Categorical variables

9. Multiple Linear Regression in Python

10. Test-train split

11. Bias Variance trade-off

12. Test train split in Python

13. Regression models other than OLS

14. Subset selection techniques

15. Shrinkage methods Ridge and Lasso

16. Ridge regression and Lasso in Python

17. Heteroscedasticity

48. Introduction to the classification Models

1. Three classification models and Data set

2. Importing the data into Python

3. The problem statements

4. Why cant we use Linear Regression

49. Logistic Regression

1. Logistic Regression

2. Training a Simple Logistic Model in Python

3. Result of Simple Logistic Regression

4. Logistic with multiple predictors

5. Training multiple predictor Logistic model in Python

6. Confusion Matrix

7. Creating Confusion Matrix in Python

8. Evaluating performance of model

9. Evaluating model performance in Python

50. Linear Discriminant Analysis (LDA)

1. Linear Discriminant Analysis

2. LDA in Python

51. K-Nearest Neighbors classifier

1. Test-Train Split

2. Test-Train Split in Python

3. K-Nearest Neighbors classifier

4. K-Nearest Neighbors in Python Part 1

5. K-Nearest Neighbors in Python Part 2

52. Comparing results from 3 models

1. Understanding the results of classification models

2. Summary of the three models

53. Simple Decision Trees

1. Introduction to Decision trees

2. Basics of Decision Trees

3. Understanding a Regression Tree

4. The stopping criteria for controlling tree growth

5. Importing the Data set into Python

6. Missing value treatment in Python

7. Dummy Variable Creation in Python

8. Dependent- Independent Data split in Python

9. Test-Train split in Python

10. Creating Decision tree in Python

11. Evaluating model performance in Python

12. Plotting decision tree in Python

13. Pruning a tree

14. Pruning a tree in Python

54. Simple Classification Tree

1. Classification tree

2. The Data set for Classification problem

3. Classification tree in Python Preprocessing

4. Classification tree in Python Training

5. Advantages and Disadvantages of Decision Trees

55. Ensemble technique 1 - Bagging

1. Ensemble technique 1 - Bagging

2. Ensemble technique 1 - Bagging in Python

56. Ensemble technique 2 - Random Forests

1. Ensemble technique 2 - Random Forests

2. Ensemble technique 2 - Random Forests in Python

3. Using Grid Search in Python

57. Ensemble technique 3 Boosting

1. Boosting

2. Ensemble technique 3a - Boosting in Python

3. Ensemble technique 3b - AdaBoost in Python

4. Ensemble technique 3c - XGBoost in Python

58. Alteryx

1. The Problem Statement

59. Case study and Alteryx Installation

1. Installing Alteryx

2. Alteryx Interface

60. DATA EXTRACTION Extracting tabular data

1. Manually entering data into Alteryx

2. Importing Data from a CSV (Comma Separated Values) file

3. Importing Data from a TXT (text) file

4. Importing Data from an Excel file

5. Importing Data from a ZIP file

6. Importing Data from multiple files in a folder

61. DATA EXTRACTION Extracting non-tabular data

1. Probable Issue with Extraction from XML.html

2.1 ProductXMLFull.csv

2.2 productxmlfull.zip

2.3 productxmlfull2.zip

2. Extracting from XML

62. Extracting from an SQL table

1. Plan for importing sales Data

2. Installing PostgreSQL and pgAdmin in your PC

3. Creating Sales table in SQL

4. Extracting from an SQL table

63. Storing and Retrieving Data Cloud storage

1. Storing Data on AWS S3

2. Importing data from AWS S3

64. Merging Data Streams

1. Union tool - Merging Customer Data

65. Data Cleansing and improving data quality

1. Find and Replace Tool

2. Data Cleaning Tool

3. Autofield and Select Tool - For controlling Field order and data type

66. Merging Sales and Product data

1. Select and Unique Tools- For Removing duplicates from product data

2. Date Parse - Changing Date format

3. Select and union - Merging Sales data

67. Sampling Data

1. Select Records Tool

2. Sample Tool

3. Random Percent Sample Tool

4. Train-Validation-Test Split sampling

68. Data Preparation

1. Multifield binning and Tile Tool - To create customer age categories

2. Formula Tool - Conditional Formula for giving category titles

3. Sort tool - Sorting customer Data based on ID

4. Formula Tool - Sales order date And ship date

5. Multifield Formula tool - Converting multiple currency fields

6. Filtering and Sorting - Positive number of days

7. Text to Columns - Splitting Product ID into 3 columns

69. Outputting Cleaned Data

1. Outputting Clean Customer And Product Data

70. Merging tables to create a datamart

1. The Joining Tool - Adding customer and Product data to Sales table

2. Extracting more info from the Date values

71. Performing Analytics Transformation on Datamart

1. The Summarize tool

2. Running Total Tool

3. Crosstab tool for creating Pivot tables

4. Transpose Tool - the opposite of Cross Tab tool

5. The Count tool

72. Creating a report in Alteryx

1. Introduction to Reporting

2. Interactive Chart tool - Bar chart to show region-wise sales

3. Interactive Chart tool - Line chart to show Sales trend

4. Table Tool - Formatting the Pivot table

5. Text Tool - Adding static text to a report

6. Visual Layout tool - Arranging charts, text and tables in a report

7. Header tool - Adding header in a report

8. Footer tool - Adding footer to a report

9. Rendering tool - rendering report as a PDF, HTML or PNG

10. Email Tool - Sending email with Alteryx

11. Image tool - Adding image to a report

12. Layout tool - Arranging charts, text or tables in a report

73. Scheduling a workflow in Alteryx

1. Schedule and Automate Alteryx workflow

74. Congratulations And about your certificate

1. Alternative to Alteryx.html

2. The final milestone!

3. Bonus Lecture.html

189,000 تومان

افزودن به سبد خرید

خرید دانلودی فوری

در این روش نیاز به افزودن محصول به سبد خرید و تکمیل اطلاعات نیست و شما پس از وارد کردن ایمیل خود و طی کردن مراحل پرداخت لینک های دریافت محصولات را در ایمیل خود دریافت خواهید کرد.

تولید کننده: Udemy-Training