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The Complete Recession Proof Excel, Machine Learning, Python
00 Mammoth Interactive Courses Introduction
00 About Mammoth Interactive (1:11)
01 How to Learn Online Effectively (13:44)
Source Files
LEVEL 0 - Course Introduction
Introduction To The Complete Recession Proof Excel, Machine Learning, Python (3:34)
LEVEL 1 - Introduction to Excel - Excel to Python Data Science Automation Masterclass - Overview
00 Course Overview - Excel To Python (7:06)
Source Files - 00 Course overview - Excel to Python
Excel to Python Data Science Automation Masterclass - 01 Excel automation with Python data modeling
00 Project Overview - Excel Automation With Python Data Modeling (0:55)
01 Read Excel File With Python (6:42)
02 Reshape Data For Data Modeling (5:29)
03 Build A Linear Regression Model With Python (5:01)
04 Visualize Machine Learning Predictor With Python (6:22)
Source FIles
Excel to Python Data Science Automation Masterclass - 02 Use Excel File in Python
01 Use Excel File In Python (9:56)
02 Manipulate Excel File With Python (4:30)
03 Build Dictionaries With Python (3:51)
Source Files - Use Excel File in Python
Excel to Python Data Science Automation Masterclass - 03 Manipulate Excel Sheets with Python
01 Import Data File Into A Pandas Dataframe (6:22)
02 Excel Sheet Manipulation With Python (6:01)
03 Get Excel Sheet Information With Python (4:15)
Source Files
Excel to Python Data Science Automation Masterclass - 04 Build Excel Filters in Python
01 Build View Excel Functions In Python (5:58)
02 Build Filter Excel Functions In Python (3:31)
03 Build Filter Functions On Blockchain Dataset (11:04)
Source Files
Excel to Python Data Science Automation Masterclass - 05 Aggregate Excel Data with Python
01 Aggregate Excel Data With Python (11:21)
02 Build Excel Pivot Tables In Python (5:19)
Source Files
Excel Expense Tracker in 15 Minutes
01 Quick Win - Track Spendings And Savings In Excel (9:58)
02 Make Your Expense Tracker More Readable (5:53)
Source Files
LEVEL 2 - Excel Data Analysis - Excel Functions Mastery Course - Intro
1.1 Introduction to the Course (8:47)
1.2 Introduction of the instructor (3:30)
1.3 Course requirements (4:03)
1.4 How to get Excel (9:33)
01 Source Files
Excel Functions Mastery Course - 02. Excel Logic and Lookup Functions Projects
2.1 What will we learn in this section (1:33)
2.2 Create An If() Function (3:24)
2.3 Nest And() Andor Or() Functions Within Reference Functions (6:37)
2.4 Work With Choose(), Vlookup(), Index(), And Match() Functions (6:19)
2.5 Create A Vlookup() Function (3:32)
2.6 Section Summary (9:37)
02 Source Files
Excel Functions Mastery Course - 03. Excel Math and Finance Functions Projects
3.1 What will we learn in this section (2:23)
3.2 Aggregate Data Using Both The Sum And Subtotal Functions (5:15)
3.3 Calculate minimums, maximums and averages from data sets (3:39)
3.4 Use the Forecast function to forecast numbers along a trend (6:57)
3.5 Generate a net present value using a formula (6:13)
3.6 Section Summary (7:38)
03 Source Files
Excel Functions Mastery Course - 04. Excel Date and Time Functions Projects
4.1 What will we learn in this section (1:14)
4.2 Work with Excel’s date manipulation functions (10:10)
4.3 Build a holiday date calculator (6:09)
4.4 Section Summary (4:43)
04 Source Files
Excel Functions Mastery Course - 05. Excel Text and Information Functions Projects
5.1 What will we learn in this section (1:59)
5.2 Split textual data apart (4:00)
5.3 Manipulate textual data (5:46)
5.4 Replace portions of textual data (4:42)
5.5 Put textual data back together with formulae (6:18)
5.6 Work with key informational functions for evaluating and responding correctly to errors in routine Excel calculations (12:00)
5.7 Use the Hyperlink function to build navigational menus inside an Excel Worksheet (4:35)
5.8 Section Summary (6:26)
05 Source Files
Excel Functions Mastery Course - 06. Excel Lists
6.1 What will we learn in this section (4:08)
6.2 How to filter items in a list (8:24)
6.3 Sorting List without messing up the data (10:09)
6.4 How to freeze rows or columns (9:53)
6.5 Remove duplicates from a list (6:51)
6.6 Section Summary (6:32)
06 Source Files
Excel Functions Mastery Course - 07. Other Excel useful functions
7.1 What will we learn in this section (2:09)
7.2 COUNT, COUNTA and COUNTIF Functions (11:57)
7.3 Create a drop down list (11:38)
7.4 Work with ISNUMBER and SEARCH functions within text functions (11:18)
7.5 Format row based on a cell value (10:54)
7.6 Create an invoice template in Excel (24:17)
7.7 Section Summary (4:46)
8.1 Course Summary and Next Steps (23:32)
07 Source Files
Introduction to PivotTables in Excel - Overview
1.1 Introduction To The Course (3:43)
1.2 Why Should You Learn Pivottables (3:17)
1.3 Introduction Of The Instructor (3:17)
1.4 Course Requirements (what Software, Experience) (6:10)
01 Source Files
Introduction to PivotTables in Excel - PivotTables Fundamental Projects
2.1 What We Learn In This Section (1:21)
2.2 What Is A Pivot Table (2:01)
2.3 Pivottables Basics (2:52)
2.4 Pivottable Compliant Data Sources (2:12)
2.5 Build A Basic Pivottable (4:17)
2.6 Section Summary (2:12)
2.7 Challenge (1:23)
02 Source Files
Introduction to PivotTables in Excel - Format PivotTables
3.1 What Will We Learn In This Section (1:01)
3.2 Introduction To Formatting Pivottables (3:29)
3.3 Build An Expense Report (6:03)
3.4 Format The Expense Report Pivottable (4:18)
3.5 Finalize The Expense Report Pivottable (5:40)
3.6 Section Summary (2:12)
3.7 Challenge (1:04)
03 Source Files
Introduction to PivotTables in Excel - Excel Tables
4.1 What Will We Learn In This Section (8:46)
4.2 What Are Excel Tables (7:23)
4.3 Sales Report Analysis With Pivottables (9:21)
4.4 Modify Source Data (3:58)
4.5 Format The Sales Report (8:38)
4.6 Complete The Sales Report Analysis (3:38)
4.7 Section Summary (3:03)
4.8 Challenge (1:46)
04 Source Files
Introduction to PivotTables in Excel - Slice and Dice Your Data
5.1 What Will We Learn In This Section-1 (1:23)
5.2 What Is Slicing Data-2 (3:41)
5.3 Slicing Data Project-3 (5:40)
5.4 Data Slicer Tools-4 (14:09)
5.5 Link Slicers To Multiple Pivottables-5 (8:03)
5.6 Section Summary-6 (2:32)
5.7 Challenge-7 (2:04)
05 Source Files
Introduction to PivotTables in Excel - Connect to Databases
6.1 What Will We Learn In This Section-1 (2:30)
6.2 Connect To Databases-3 (2:06)
6.3 Import Data Sources-4 (3:58)
6.4 Use Pivottables To Refine Data-5 (4:41)
6.5 Consolidate Your Data Table-6 (3:17)
6.6 Format Large Data Sets-7 (4:51)
6.7 Slicer And Timeline In Large Data Sets-8 (4:36)
6.8 Refresh And Drill Down From Databases-9 (4:46)
6.9 Section Summary-10 (4:01)
6.10 Challenge-2 (2:01)
06 Source Files
Excel Charts and Visualization - 01. Intro to course
1.1 Introduction To The Course-1 (4:46)
1.2 Why Should You Learn About Charts And Data Visualization-2 (4:31)
1.3 Introduction Of The Instructor-3 (2:08)
1.4 Course Requirements (what Software, Experience)-4 (2:36)
Excel Charts and Visualization - 02. Charts and Basics
2.1 What Will We Learn In This Section-1 (1:21)
2.2 Main Principles And Chart Visualization Impact-2 (2:38)
2.3 Choosing The Correct Chart-3 (1:56)
2.4 Communicate With The End User-4 (2:18)
2.5 Section Summary-5 (2:59)
2.6 Challenge-6 (2:12)
Excel Charts and Visualization - 03 Excel Chart Tools
3.1 What Will We Learn In This Section-1 (1:35)
3.2 Chart Design-2 (6:38)
3.3 Working With Chart Formats-3 (4:35)
3.4 Chart Types-4 (2:08)
3.5 Primary & Secondary Axis-5 (4:20)
3.6 Chart Templates-6 (3:25)
3.7 Section Summary-7 (2:50)
3.8 Challenge-8 (1:23)
Excel Charts and Visualization - 04 Working with Basic Excel Charts & Graphs
4.1 What Will We Learn In This Section (1:20)
4.2 Excel Column Charts (4:13)
4.3 Column Charts Challenge (1:08)
4.4 Excel Bar Charts 1 (3:12)
4.5 Bar Charts Challenge (0:48)
4.6 Excel Line Charts-36 (3:52)
4.7 Line Charts Challenge-37 (0:48)
4.8 Excel Pie Charts-38 (5:01)
4.9 Pie Charts Challenge-39 (0:57)
4.10 Excel Area Charts-3 (2:27)
4.11 Area Charts Challenge-4 (0:50)
4.12 Excel Scatter Charts-5 (4:00)
4.13 Scatter Charts Challenge-6 (0:41)
4.14 Excel Bubble Charts-7 (5:12)
4.15 Bubble Charts Challenge-8 (0:54)
4.16 Excel Stock Charts-9 (3:07)
4.17 Stock Charts Challenge-10 (0:56)
4.18 Excel Surface Charts-11 (4:42)
4.19 Surface Charts Challenge-12 (0:43)
4.20 Excel Radar Charts-14 (2:58)
4.21 Radar Charts Challenge-15 (0:38)
4.22 Excel Treemap Charts-16 (2:31)
4.23 Treemap Charts Challenge-17 (1:03)
4.24 Excel Sunburst Charts-18 (2:36)
4.25 Sunburst Charts Challenge-19 (0:59)
4.26 Excel Histogram & Pareto Charts-20 (4:02)
4.27 Histogram & Pareto Charts Challenge-21 (1:04)
4.28 Excel Waterfall Charts-22 (5:26)
4.29 Waterfall Charts Challenge-23 (0:46)
4.30 Excel Box&whisker Charts-24 (3:24)
4.31 Box&whisker Charts Challenge-25 (1:03)
4.32 Excel Sparklines-26 (3:44)
4.33 Sparklines Challenge-27 (0:53)
4.34 Excel Color Scales-28 (3:42)
4.35 Color Scales Challenge-29 (0:49)
4.36 Excel 3D Map (4:35)
4.37 3D Map Challenge (1:45)
4.38 Section Summary (10:13)
04 Source Files
Excel Charts and Visualization - 05. Excel Advanced Data Visualization
5.1 What Will We Learn In This Section-1 (2:23)
5.2 Data Visualization With Pivot Chart And Slicers-7 (7:04)
5.3 Challenge Data Visualization With Pivot Chart And Slicers-8 (1:34)
5.4 Create Break Even Chart-9 (9:24)
5.5 Challenge Break Even Chart-10 (1:11)
5.6 Rating Star Chart-11 (7:09)
5.7 Challenge Star Rating-12 (1:28)
5.8 Drop Down Menu For Chart-13 (16:30)
5.9 Challenge Drop Down Menu Chart-14 (1:20)
5.10 Risk Score Chart-2 (11:03)
5.11 Challenge Risk Score Chart-3 (1:22)
5.12 Dynamic Chart Update (8:10)
5.13 Challenge Dynamic Chart Update (1:47)
5.14 Section Summary (6:48)
6.1 Course Summary And Next Steps (16:29)
Excel Financial Analysis - 01. Introduction to the Course
1.1 Introduction To The Course (4:16)
1.2 Why Should You Learn Financial Analysis (4:22)
1.3 Introduction Of The Instructor (6:24)
1.4 Course Requirements (what Software, Experience) (5:46)
Excel Financial Analysis - 02. Excel Statement Models
2.1 What Will We Learn In This Section (2:35)
2.2 Preparing Data Source For P&l (16:08)
2.3 Create P&l Structure (13:27)
2.4 Adding Data To P&l (19:48)
2.5 Calculating Variances (11:51)
2.6 Balance Sheet Structure (10:43)
2.7 Adding Values On Bs From Different Files Format (20:38)
2.8 Cash Flow Structure (10:25)
2.9 Calculating Cash Flow (11:04)
2.10 Challenge (1:35)
Excel Financial Analysis - 03. Excel Finance Methods
3.1 What Will We Learn In This Section (5:48)
3.2 Forecast With Scenarios (23:30)
3.3 How To Calculate Finance Main KPI's (15:38)
3.4 Fixed Assets Roll Forward (18:29)
3.5 Loan Schedule (13:54)
3.6 Accounts receivable Management Basics (20:49)
3.7 Customers Rank (11:56)
3.8 Create Budgets Categories (19:45)
3.9 Challenge (1:25)
4.1 Course Summary And Next Steps (31:21)
Data Visualization - 01. Introduction to the Course
1.1 Introduction To The Course-1 (8:27)
1.2 Introduction Of The Instructor-2 (3:11)
1.3 Course Requirements-3 (2:59)
1.4 How To Get Excel-4 (4:13)
Source files
Data Visualization - 02. Dashboards Introduction
2.1 What Will We Learn In This Section-1 (1:20)
2.2 What Are Dashboards-2 (5:39)
2.3 Answers You Need Before You Start A Dashboard-3 (7:45)
2.4 Best Practices For Dashboard Layout-4 (4:42)
2.5 Best Practices For Dashboard Colors-5 (3:54)
2.6 Section Summary-6 (3:40)
Source Code
Data Visualization - 03. Build a Dashboard Project
3.1 What will we learn in this section (1:16)
3.2 Build a Wireframe in Excel (5:42)
3.3 Prepare Raw Data for Dashboard (5:57)
3.4 Prepare Calculation sheet (13:01)
3.5 Section Summary (6:08)
Source Code
Data Visualization - 04. Scrolling Data Table
4.1 What will we learn in this section (2:48)
4.2 Build a Combo Box (10:44)
4.3 Complex Lookup (14:36)
4.4 Build a Scrolling Data Table (11:40)
4.5 Conditionally Format Actual Values vs Budgeted Values (10:52)
4.6 Conditional Headers (9:25)
4.7 Section Summary (3:01)
Source Code
Data Visualization - 05. Show Top Indicators
5.1 What will we learn in this section (1:50)
5.2 Show Top Matches Over and Under Budget (9:20)
5.3 List Box to Select Indicators (5:11)
5.4 Toggle Between Top Over or Under (12:50)
5.5 Section Summary (2:19)
Source Code
Data Visualization - 06. Scrollable Line Chart
6.1 What will we learn in this section (3:20)
6.2 Prepare Data for Scrolling Chart (14:19)
6.3 Scrollable Line Chart (11:17)
6.4 Remove Crashing Lines (4:12)
6.5 Toggle Visibility of Line Series (9:56)
6.6 Finetune the Line Series (7:08)
6.7 Section Summary (5:34)
Source Code
Data Visualization - 07. Interactivity
7.1 What will we learn in this section (1:56)
7.2 Add Interactivity to Reports with Pivot Slicers (10:44)
7.3 Column Chart Controlled by Slicer (6:47)
7.4 Pivot SLicer Sorting (4:26)
7.5 Select Only 1 Slicer (2:13)
7.6 Dynamic Comments with SLicers (11:36)
7.7 Section Summary (2:58)
Source Code
Data Visualization - 08. Finetune the Dashboard
8.1 What will we learn in this section (1:01)
8.2 Add Calculations for Variances in Pivot Tables (4:23)
8.3 Conditional Formatting in Pivot Tables (7:04)
8.4 Refresh Pivot Table with Easy VBA (7:49)
8.5 Section Summary (2:33)
Source Code
9.1 Course Summary and Next Steps (10:27)
LEVEL 3 - Power BI and Power Query - Beginners Excel Power Query and M Masterclass - 01 Course Overview
01 What Are Power Query And M (8:16)
02 Course Overview (6:16)
Source Files
Beginners Excel Power Query and M Masterclass - 02 Build your first M queries
01 Capitalize A Table Column (6:39)
02 Build An Expression With Let (17:09)
Source Files
Beginners Excel Power Query and M Masterclass - 03 Join tables with M
01 Build And Reference Tables (8:08)
02 Append And Combine Tables (5:33)
03 Inner Join Tables (5:33)
Join tables with M - Source Files
Beginners Excel Power Query and M Masterclass - 04 Build M functions to perform tasks
01 Build M Functions To Perform Tasks (8:13)
02 Call Functions (5:10)
03 Use The Each Keyword (2:33)
04 Change A Table With A Function (7:30)
05 Loop An Action With A Recursive Function (8:02)
06 Calculate Price After Discount 1 (6:09)
07 Use Optional Parameters To Combine Text (5:13)
08 Transform A List With A Function (2:09)
09 Calculate Number Of Working Days (12:20)
Build M functions to perform tasks - Source Files
Beginners Excel Power Query and M Masterclass - 05 Work with lists in M
01 Build A List With Each (5:16)
02 Concatenate Items In A List (5:01)
03 Iterate Over A List (4:17)
04 Iterate Over A List With Recursion (3:26)
Source Files
Beginners Excel Power Query and M Masterclass - 06 Build M variables to store data
01 Calculate Affiliate Revenue (4:37)
02 Variable Types (5:49)
03 Variable Scope - Where Can You Use Variables (8:57)
04 Order Of Evaluation (5:18)
Source Files
Beginners Excel Power Query and M Masterclass - 07 Aggregate table data with M
01 Count Rows (7:32)
02 Calculate Profits Per Quarter (5:55)
03 Group Similar Rows (5:59)
04 Sort A Table (5:27)
05 Query Data From Another Spreadsheet (7:18)
06 Find Where Sales Met Quota (2:55)
Source Files
Beginners Excel Power Query and M Masterclass - 08 Work with tables in M
01 Build Tables (6:55)
02 Work With Tables (5:37)
03 Fill In A Table (3:27)
Source Files
Beginners Excel Power Query and M Masterclass - 09 Build conditions with M if expressions
01 Build Conditions With If Expressions (8:14)
Source Files
Beginners Excel Power Query and M Masterclass - 10 Work with M data types
01 Manipulate Text (11:34)
02 Work With Numbers (3:00)
03 Work With Date, Time And Duration (7:52)
Source Files
Beginners Excel Power Query and M Masterclass - 11 Build queries for tables with M
01 Filter A Table By Row (6:59)
02 Format A List Of Values Into A Table (7:57)
Build queries for tables with M - Source Files
Beginners Excel Power Query and M Masterclass - 12 Build calculations for tables with M
01 Build Address Labels (8:26)
02 Calculate Percentage Of Total (6:44)
03 Calculate Sales Rank (7:04)
04 Count Number Of Distinct Rows (6:59)
Source Files
Beginners Excel Power Query and M Masterclass - 13 Fetch data from the web with M
01 Query Tables From The Web (7:15)
02 Search For Links On The Web (8:09)
03 Check If A Webpage Exists (6:24)
Source Files
Advanced Excel Power Query and M Masterclass - 00 Course overview
00 Course Overview - Advanced Excel Power Query And M (4:09)
01 What Are Power Query And M (8:15)
Course overview - Source Files
Advanced Excel Power Query and M Masterclass - 01 Build expressions with let
01 Build Nested Let Expressions (3:53)
02 Build A List With A Sequence (2:43)
03 Build An Unnamed Record (4:14)
Build expressions with let - Source Files
Advanced Excel Power Query and M Masterclass - 02 Build expressions with each
01 Work With The Each Keyword (5:00)
02 Generate A List (5:40)
03 Find An Entry In A Record (2:16)
04 Select Items From A List (5:06)
05 Serialize A Column (13:43)
06 Find Best Match Of Values (21:49)
Build expressions with each - Source Files
Advanced Excel Power Query and M Masterclass - 03 Build M functions to perform tasks
01 Build A Function (3:21)
02 Build A Closure (6:27)
03 Build A Function In A Record (4:23)
04 Count Fibonacci Numbers With A Recursive Function (7:04)
05 Remove Html Tags (9:19)
06 Build A For Each Loop (9:37)
Build M functions to perform tasks - Source Files
Advanced Excel Power Query and M Masterclass - 04 Work with tables in M
01 Select A Column From A Table (3:40)
02 Select A Value At A Row And Column (3:05)
03 Select Row Where A Condition Is Met (3:53)
04 Cross Join Tables (8:40)
05 Join Tables On A Key (5:48)
06 Change Column Types (3:48)
07 Fill A Table With Random Values (7:12)
Work with tables in M - Source Files
Advanced Excel Power Query and M Masterclass - 05 Pivot a table
00 What Is Pivoting (1:28)
01 Pivot A Table (12:05)
Pivot a table - Source Files
Advanced Excel Power Query and M Masterclass - 06 Build expressions with evaluate
01 Build An Expression With Evaluate (3:06)
02 Build A Nested Evaluate Expression (3:04)
03 Use Global Library Functions (2:27)
Build expressions with evaluate - Source Files
Advanced Excel Power Query and M Masterclass - 07 Work with matrices in M
00 How To Multiply Matrices (3:03)
01 Build Matrices In M (4:32)
02 Multiply Matrics (17:45)
Work with matrices in M - Source Files
Beginners Microsoft Power BI, DAX and Power Query with Artificial Intelligence - 01. Introduction To The Course
1.1 Introduction To Power BI (7:08)
Source Files
Beginners Microsoft Power BI, DAX and Power Query with Artificial Intelligence - 02. Get Started in Power BI
2.1 Installing Power BI (5:10)
2.2 Getting Started With PowerbI (16:17)
Source Files
Beginners Microsoft Power BI, DAX and Power Query with Artificial Intelligence - 03. Get Started in the Power Query Editor
3.1 Power Query Editor (8:53)
3.2 Getting Started With Power Query Editor (24:18)
Source Files
Beginners Microsoft Power BI, DAX and Power Query with Artificial Intelligence - 04. Work with Data in Power Query
4.1 Working With Data In Power Query (16:29)
4.2 Working With Data In Power Query (19:08)
4.3 Working With Data In Power Query Editor (13:32)
Source Files
Beginners Microsoft Power BI, DAX and Power Query with Artificial Intelligence - 05. Build Tables
5.1 Fact And Dimension Table (14:48)
5.2 Building Tables (7:41)
5.3 Date Dim Extract And Transform (8:42)
5.4 Extract Functionalities (6:05)
Beginners Microsoft Power BI, DAX and Power Query with Artificial Intelligence - 06. Analyze Data With Dax In Power BI
6.1 Data Analysis Expression Dax In Power BI (7:04)
6.2 Working With Data Analysis Expression DAX (12:16)
6.3 Measures Filters (10:00)
6.4 Measures All (6:06)
6.5 Iterators (6:30)
6.6 Iterators2 (7:36)
6.7 Iterators3 (8:27)
Source Files
Beginners Microsoft Power BI, DAX and Power Query with Artificial Intelligence - 07. Work with DAX Functions and Operators
7.1 Time Intelligence DAX (9:04)
7.2 Time Intelligence Functions (8:33)
7.3 Demo And Examples (9:25)
7.4 Date Table (4:31)
Source Files
Beginners Microsoft Power BI, DAX and Power Query with Artificial Intelligence - 08. Artificial Intelligence With Power BI
8.1 AI With PowerBI-1 (21:43)
8.2 AI With PowerBI-2 (19:27)
8.3 AI With PowerBI-3 (22:12)
Source Files
LEVEL 4 - Excel Automation Programming - Beginners Excel VBA - 01-02 Course Introduction
01.00 Course Overview (2:24)
01.01 How To Save Macros (1:34)
01-02 Source Files
Beginners Excel VBA - 03 Send Messages with MsgBox
03.00 Topics Overview (0:53)
03.01 Build A Simple Message (3:34)
03.02 Build An Advanced Message (5:10)
03.03 Empty A Sheet With The Msgbox Function (6:44)
03.04 Prompt User For Input (7:29)
03 Source Files
Beginners Excel VBA - 04 Workbook and Worksheet Object
04.00 Topics Overview (1:30)
04.01 Object Hierarchymp4 (5:10)
04.02 Change Multiple Worksheets (7:05)
04.03 Add And Count Worksheets (6:01)
04.04 Get Path Of A Workbook (5:14)
04.05 Open And Close Workbooks (8:41)
04.06 Loop Through Worksheets And Workbooks (8:19)
04.07 Build A Sales Calculator (11:53)
04.08 Change Charts (10:30)
04 Source Files
Beginners Excel VBA - 05 Work with the Range Object
05 Source Files
05.00 Topics Overview (1:22)
05.01 Program A Range Of A Spreadsheet (6:55)
05.02 Use Cells Instead Of A Range (6:04)
05.03 Use A Range Variable (6:04)
05.04 Select A Range (4:52)
05.05 Access A Row (4:35)
05.06 Copy And Paste A Range (8:45)
05.07 Clear A Range (3:59)
05.08 Count A Range (4:21)
Beginners Excel VBA - 06 Work with Range Properties
06.00 Topics Overview (1:03)
06.01 Find The Current Region Of A Cell (7:23)
06.02 Dynamic Range Program (7:11)
06.03 Resize A Range (2:30)
06.04 Select Entire Rows And Columns (6:33)
06.05 Offset Property (3:32)
06.06 End Property (5:06)
06 Source Files
Beginners Excel VBA - 07 More Range Projects
07.00 Topics Overview (1:21)
07.01 Union And Intersect Of Ranges (4:24)
07.02 Detect Content (5:37)
07.03 Build A Range Program (5:47)
07.04 Change Text Color (4:30)
07.05 Bold A Range (2:39)
07.06 Change Cell Color (5:04)
07.07 Work With Areas (4:55)
07.08 Find Differences In Ranges (8:17)
07 Source Files
Beginners Excel VBA - 08 Variables
08.00 Topics Overview (1:38)
08.01 Integer Data Type (2:58)
08.02 String Data Type (2:20)
08.03 Double Data Type (2:54)
08.04 Boolean Data Type (4:05)
08.05 Retain Variable Value (2:54)
08 Source Files
Beginners Excel VBA - 09 Work with Conditionals
09.00 Topics Overview (1:26)
09.01 If Then Statement (4:38)
09.02 Else Statement (4:55)
09 Source Files
Beginners Excel VBA - 10 Work with AND, OR and NOT
10.00 Topics Overview (1:21)
10.01 Greeting Program - Logical Operator And (4:00)
10.02 Logical Operator OR (5:36)
10.03 Logical Operator NOT (3:15)
10 Source Files
Beginners Excel VBA - 11 Build Conditionals Projects
11.00 Topics Overview (1:58)
11.01 Select Case (5:42)
11.02 Build A Commission Calculator Project (6:11)
11.03 Find Remainder With Mod (3:11)
11.04 Check Number Program (6:38)
11.05 K Smallest Value Program (6:54)
11.06 Group By Font Style (6:45)
11.07 Remove Empty Cells (5:26)
11 Source Files
Intermediate Excel VBA - Overview & Introduction to Loops
12.00.00 Course Overview (2:50)
12.00 Topics Overview (0:57)
12.01 Single Loop (5:59)
12.02 Double Loop (5:14)
12.03 Triple Loop (6:24)
12.04 Do While Loop (5:34)
12.05 Build A Commission Table (5:33)
12 Source Files
Intermediate Excel VBA - 13 Loop Projects
13.00 Topics Overview (1:40)
13.01 Loop Through Defined Range (3:37)
13.02 Loop Through Entire Column (3:29)
13.03 Do Until Loop (3:22)
13.04 Use Step To Increment (4:22)
13.05 Build A Pattern Project (4:49)
13.06 How To Sort (5:32)
13.07 Sort By Related Data (8:15)
13.08 Delete Duplicate Values (6:10)
Source Files
Intermediate Excel VBA - 14 String Manipulation
14.00 Topics Overview (1:28)
14.01 Join Strings (3:13)
14.02 Extract Substrings From Left Or Right (3:07)
14.03 Extract Substring At Middle (4:12)
14.04 Get Length Of A String (2:40)
14.05 Get Substring Position (3:16)
14.06 How To Split Strings (4:56)
14.07 Reverse Characters (4:10)
14.08 Change String Casing (3:28)
14.09 Count Words In A Range (8:17)
Source Files
Intermediate Excel VBA - 15 Build Custom Functions
15.00 Topics Overview (1:19)
15.01 Make And Use Your Own Function (6:33)
15.02 Pass Arguments To A Function (7:43)
15.03 Custom Calculator Function (6:22)
Source Files
Intermediate Excel VBA - 16 Build Arrays
16 Source Files
16.00 Topics Overview (1:18)
16.01 One Dimensional Array (5:46)
16.02 Two Dimensional Array (6:26)
16.03 Change Array Size (4:54)
16.04 Build An Array (5:09)
16.05 Populate Row With Array (3:21)
16.06 Array Length (6:47)
16.07 Split String Into An Array (4:28)
16.08 Join Array Into A String (3:49)
Intermediate Excel VBA - 17 Work with Dates
17.00 Topics Overview (1:12)
17.01 Delay A Procedure (4:12)
17.02 Schedule A Procedure (4:18)
17.03 Count Years (5:20)
17.04 Count Days Between Dates (2:41)
17.05 Count Weekdays Between Dates (4:51)
17.06 Sort Dates (6:27)
17 Source Files
Intermediate Excel VBA - 18 Application Object
18 Source Files
18.00 Topics Overview (1:36)
18.01 How To Access Excel Functions (4:28)
18.02 Disable Screen Updating (3:19)
18.03 Disable Alerts (3:38)
18.04 Show Progress Of Macro (6:35)
18.05 Read Data From A File (6:35)
18.06 Write Data To A File (5:10)
Intermediate Excel VBA - 19 VBA Projects
19.00 Topics Overview (0:52)
19.01 Build A Table (4:47)
19.02 Build A Table Of Contents (11:47)
19.03 Build A Table Of Contents 2 (4:42)
19.04 Combine Worksheets (17:42)
19.05 Combine Worksheets By Column (15:48)
19 Source Files
Intermediate Excel VBA - 20 Programming Charts
20.00 Topics Overview (1:20)
20.01 Program A Chart (6:12)
20.02 Program An Embedded Chart (4:59)
20.03 Delete Charts Programatically (2:19)
20 Source Files
Python Language Fundamentals
02. Variables (19:17)
03. Type Conversion Examples (10:04)
04. Operators (7:04)
05. Operators Examples (21:52)
06. Collections (8:23)
07. Lists (11:38)
08. Multidimensional List Examples (8:05)
09. Tuples Examples (8:34)
10. Dictionaries Examples (14:24)
11. Ranges Examples (8:30)
12. Conditionals (6:41)
13. If Statement Examples (10:16)
14. If Statement Variants Examples (11:18)
15. Loops (7:00)
16. While Loops Examples (11:30)
17. For Loops Examples (11:18)
18. Functions (7:47)
19. Functions Examples (9:16)
20. Parameters And Return Values Examples (13:46)
21. Classes And Objects (11:13)
22. Classes Example (13:11)
23. Objects Examples (9:54)
24. Inheritance Examples (17:26)
25. Static Members Example (11:03)
26. Summary And Outro (4:06)
Source Files
Automate Excel Files with Python OpenPyXL - 01 Introduction to the Course
01.00 Course Overview (2:20)
01.01 Run Openpyxl on the Web (1:45)
Source Files
Automate Excel Files with Python OpenPyXL - 02 Use OpenPyXL and Sheets
02.01 Make a Workbook (11:01)
02.02 Save a Workbook (3:51)
02.03 Read a Workbook (8:02)
02.04 Work with Rows and Columns (8:07)
02.05 Use a Formula (8:41)
02.06 Use Dates (7:18)
02.07 Merge and Unmerge Cells (7:11)
02.08 Fold a Range (6:17)
02.09 Make a New Sheet (3:17)
02.10 Copy Data to a Sheet (4:35)
02.11 Remove a Sheet (3:45)
02 Source Files
Automate Excel Files with Python OpenPyXL - 03.01 Worksheet Tables
03.01 Build a Table (15:50)
03.02 Style a Table (8:55)
Source Files
Automate Excel Files with Python OpenPyXL - 03.02 Format Cells
03.01 Import Dataset (4:19)
03.02 Style a Cell (6:47)
03.03 Make a Named Style (6:57)
03.04 Copy a Style (4:59)
Source Files
Automate Excel Files with Python OpenPyXL - 04 Build 2D Charts
04.01 Make a Chart (11:04)
04.02 Build Line Charts (15:30)
04.03 Build a Pie Chart (14:09)
04.04 Build a Scatter Chart (11:22)
04.05 Build an Area Chart (8:21)
04 Source Files
Automate Excel Files with Python OpenPyXL - 05 Project_ Employee Timelog
05.01 Project Setup (4:29)
05.02 Expand Columns to Fit Content (6:35)
05.03 Add Dates (7:34)
05.04 Add Days of the Week (7:11)
05 Source Files
Automate Excel Files with Python OpenPyXL - 06 Write to a Text File
06.01 Read Spreadsheet Data (7:11)
06.02 Store Spreadsheet Data (3:39)
06.03 Write to a Text File (5:22)
06 Source Files
Automate Excel Files with Python OpenPyXL - 07 Update a Spreadsheet
07.01 Set Up Update Information (3:44)
07.02 Update the Spreadsheet (5:41)
07 Source Files
Automate Excel Files with Python OpenPyXL - 08 More Chart Types
08.01 Build a Stock Chart (9:13)
08.02 Build a Doughnut Chart (9:22)
08.03 Build a Bubble Chart (8:53)
08 Source Files
Automate Excel Files with Python OpenPyXL - 09 Web Scraping
09.01 Import Web Driver (8:06)
09.02 Scrape a Web Page (6:06)
09.03 Parse Page Data (9:17)
09.04 Put Data into Excel Sheet (6:22)
09.05 Clean Data (4:38)
09 Source Files
Web Automation with Selenium Python - 00 Getting Started with Selenium
00.00 What You'll Learn (5:42)
00.01 Install Selenium (9:11)
00.02 Download Visual Studio Code (4:10)
00 Source Files
Web Automation with Selenium Python - 01 Automate Finding Elements
01.01 Find Elements By Name (14:50)
01.02 Find Elements By Id (7:34)
01.03 Find Elements By Xpath (12:29)
01.04 Find Input Field By Xpath (13:44)
01.05 Find Elements By Css Selector (9:14)
01.06 Find Elements By Link Text (7:47)
01.07 Find Elements By Partial Link Text (8:05)
01.08 Find Elements By Classname (6:22)
01.09 Find Elements By Tagname (7:29)
01 Source Files
Web Automation with Selenium Python - 02 Beginner's Automation with Selenium
02.01 Automate A Google Search (19:41)
02.02 Automate Navigating A Dropdown Menu (16:22)
02.03 Automate Changing Tabs (15:41)
02.04 Automate Alert Popups (13:26)
02 Source Files
Web Automation with Selenium Python - 03 Avoid Errors with Waits
03.01 Explicit Waits (21:03)
03.02 Implicit Waits (8:45)
03 Source Files
Web Automation with Selenium Python - 04 Automate Browsers Commands
04.01 Automate Window Size (12:04)
04.02 Get Title And URL (4:12)
04.03 Automate Closing Vs Quitting Windows (4:06)
04 Source Files
Web Automation with Selenium Python - 05 Automate Mouse Actions
05.01 Mouse Hover (14:01)
05.02 Automate Mouse Click (7:39)
05.03 Right Click (6:26)
05.04 Automate Double Click (8:36)
05.05 Click, Hold And Release (7:17)
05 Source Files
Web Automation with Selenium Python - 06 Automate Images
06.01 Web Scrape Images (13:29)
06.02 Automate Downloading Images (27:34)
06 Source Files
The Ultimate Amazon Honeycode Guide - 01 Introduction to Course
01 Course Overview (4:00)
02 How To Sign Up (1:21)
03 Beta (0:46)
The Ultimate Amazon Honeycode Guide - 02 Build Your First App
01 Project Overview (5:48)
02 Set Up Data Tables (10:26)
03 Build Your First App (12:12)
04 Customize App And Add Navigation (7:54)
05 Add Automated Notifications (9:38)
The Ultimate Amazon Honeycode Guide - 03 Build an App Backwards with Data
01 Project Overview (2:27)
02 Format Data (22:14)
03 Build The App (23:48)
04 Style And Customize The App (20:31)
05 Automation And Edge Cases (10:38)
The Ultimate Amazon Honeycode Guide - 04 Content Tracker
01 Content Tracker Overview (4:49)
02 Content Tracker Database (13:29)
The Ultimate Amazon Honeycode Guide - 05 Build Apps with Objects
01 Data Cell (15:34)
02 Content Box (5:25)
03 Button (9:53)
04 Blank Block (4:04)
05 Blank List (13:24)
06 Column List (7:47)
07 Stacked List (8:21)
08 Form (7:35)
09 Input Field (6:57)
10 Picklist (8:12)
11 Number (6:13)
12 Percentage (5:06)
13 Currency (3:15)
14 Contact (4:37)
15 Date (4:25)
16 Segment (3:53)
17 Screen (4:39)
The Ultimate Amazon Honeycode Guide - 06 Simple Survey
01 Simple Survey Overview (4:45)
02 Simple Survey Database (5:50)
The Ultimate Amazon Honeycode Guide - 07 Inventory Management
01 Inventory Management Overview (7:06)
02 Inventory Management Database (12:57)
The Ultimate Amazon Honeycode Guide - 08 To Do List
01 To Do List Overview (4:34)
02 To Do List Database (11:12)
LEVEL 5 - Blockchain Cryptocurrency and Machine Learning - Truffle Fullstack dApp Development with React, Solidity and JavaScript
00 Course Overview - Truffle Fullstack Dapp Development (6:02)
Source Files
Truffle Fullstack dApp Development with React, Solidity and JavaScript - 01a Introduction to Blockchain (Prerequisite)
00 Blockchain Introduction (8:32)
01 What Are Blockchains And Distributed Ledgers (3:48)
02 What Are Bitcoin And Ethereum (5:28)
Truffle Fullstack dApp Development with React, Solidity and JavaScript - 01b (Prerequisite) Introduction to Solidity
01 Introduction To Ethereum Remix IDE (8:12)
01b (Prerequisite) Introduction to Solidity - 02 Build Your First Solidity Smart Contract
01 Build Your First Contract-1 (8:48)
02 Change A State Variable Value-2 (5:55)
Source Files
01b (Prerequisite) Introduction to Solidity - 03 Build Solidity Variables
01 Build A Local Variable-1 (4:28)
02 Build State Variables Of Different Data Types-2 (10:54)
03 Build A Custom Data Type With A Struct-3 (4:47)
Source Files
01b (Prerequisite) Introduction to Solidity - 04 Build Solidity Arrays
01 Build Arrays-1 (11:07)
02 Build Array Functions-2 (6:17)
Source Files
01b (Prerequisite) Introduction to Solidity - 05 Build Solidity Mappings
01 Build A Mapping-1 (6:20)
02 Build A Database-Like Mapping-2 (7:42)
03 Assign Ownership To Individual Ethereum Addresses-3 (4:59)
Source Files
01b (Prerequisite) Introduction to Solidity - 06 Build Solidity Conditionals and Loops
01 Build A Conditional-1 (6:57)
02 Build A Loop-2 (9:25)
Source Files
01b (Prerequisite) Introduction to Solidity - 07 Send Ether
01 Send Ether-1 (8:31)
Source Files
01b (Prerequisite) Introduction to Solidity - 08 Build Smart Contracts
00 Build A Profit Splitter Contract-1 (11:48)
01 Build A Contract With Limited Addresses-2 (11:40)
02 Build A Contract And Library-3 (15:01)
03 Build A Contract With A Limited Time Transaction-4 (10:20)
04 Build Contracts With Inheritance-5 (13:22)
05 Build Contracts With Visibility Modifiers-6 (10:50)
06 Build A Contract With Mutability Modifiers-7 (10:20)
07 Build An Abstract Contract-8 (13:09)
08 Build A Bank Contract-9 (9:25)
09 Access Struct Value-10 (4:13)
Source Files
01c (Prerequisite) Command Line Fundamentals - 01 Course Overview
01 Why All Developers Need To Know The Command Line (8:50)
03 What Are Linux And Unix Terminals (8:04)
01c (Prerequisite) Command Line Fundamentals - 02 What you'll need
01 What You'll Need (1:20)
02 Install Linux Command Line On Windows (3:18)
01c (Prerequisite) Command Line Fundamentals - 03 Use Commands in a Linux Unix Terminal
01 Build Your First Command In The Command Line (3:48)
02 Navigate Directories In The Command Line (6:33)
03 Build And Edit A New File In The Command Line (7:27)
04 Move Files In The Command Line (9:00)
01d (Prerequisite) Install Node and NPM
00 What Is Node Js-1 (8:22)
01 Install Node And Npm On Mac Or Windows-2 (3:14)
02 How To Install Node And Npm On Windows (8:41)
Source files
Truffle Fullstack dApp Development - 02 Build blockchain backend for social media smart contracts
00 What Is Truffle Ethereum (1:29)
01 Start A Social Media Dapp (6:13)
02 Build Social Media Smart contract (9:19)
Lecture 01 Source Files
Lecture 02 Source Files
Truffle Fullstack dApp Development - 04 Deploy social media smart contract to blockchain
00 What Is Ganache (1:41)
Source Files
Truffle Fullstack dApp Development - 05a (Prerequisite) Introduction to HTML
01. Course Requirements (2:55)
02. What Is Jsbin (3:15)
03. Setting Up The Html Document (2:41)
04. Header Tags And Paragraphs Tags (4:06)
05. Styles (3:32)
06. Bold Underline And Italic Tags (3:10)
07. Adding In A Link (1:38)
08. Adding In A Image (3:00)
09. Adding A Link To An Image (1:54)
10. Lists (4:03)
11. Tables (3:29)
12. Different Kinds Of Input (4:59)
13. Adding In A Submit Button (3:01)
Truffle Fullstack dApp Development - 05b (Prerequisite) Introduction to JavaScript
01. Variables (5:36)
02. JavaScript (10:24)
03. Numbers (4:52)
04. Booleans (5:22)
05. If Statements (4:27)
06. Arrays (8:31)
07. For Loops (9:16)
08. While Loops (4:33)
09. Objects (8:02)
10. Functions (6:09)
11. Foreach (3:54)
12. Map Functions (5:22)
13. Using Objects As Dictionary (2:45)
14. Switch Statements (6:38)
15. Destructuring-1 (5:30)
16. Spread Operator-1 (6:56)
17. String Templates-1 (6:37)
18. Error Handling-1 (5:45)
19. Let And Const Keywords-1 (3:39)
20. Do-while-1 (1:45)
21. Sets-1 (5:42)
22. Maps-1 (4:39)
23. Stacks-1 (6:06)
24. Queues-1 (11:49)
25. For Loop (5:11)
26. Recursive Functions-1 (7:13)
27. Loop Labeling-1 (5:18)
28. 2d Arrays-1 (21:59)
29. Settimeout-1 (7:02)
30. Sentimental-1 (11:21)
31. Functions With Optional Parameters-1 (15:10)
32. Basic Regular Expression-1 (5:53)
33. Handle Keypress Events-1 (22:45)
34. Priority Queue-1 (15:54)
35. Add and delete Object Property-1 (2:44)
37. Concat-1 (3:12)
38. Flat And Flatmap-1 (2:06)
Truffle Fullstack dApp Development - 06 (Prerequisite) Introduction to React
00 Why You Should Learn React (5:30)
01 React Introduction (12:32)
02 Set up a Container (8:13)
03 Generate a List (6:46)
04 Add Items to the List (6:34)
05 Clear Input Field (10:26)
06 Remove a Task (10:39)
Source Files
Truffle Fullstack dApp Development - 06b Web3 and MetaMask Introduction
01 What Is Web3js (2:06)
02 Install Metamask (2:14)
Truffle Fullstack dApp Development - 07 Connect to smart contract in app with Web3
01 Load Web3 And Smart Contract In Javascript Frontend (11:46)
02 Launch React Dapp With Ganache And Metamask (5:45)
Lecture 01 Source Files
Lecture 02 Source Files
Truffle Fullstack dApp Development - 08 Build Add Social Media Post component
01 Build Add Social Media Post Component (5:18)
02 Use Addpost React Component In App (10:01)
Source files
Truffle Fullstack dApp Development - 09 Build posts and likes components
01 Build Social Media Posts Component (10:30)
02 Enable Likes In Social Media Dapp (9:47)
Source files
Blockchain and Cryptocurrency Machine Learning - 00a Course Overview
00 Course Overview - Blockchain Machine Learning (9:14)
Source Files
Blockchain and Cryptocurrency Machine Learning - 00b What is Blockchain
00 How Blockchain Was Invented (7:26)
01 Blockchain Introduction (8:32)
02 What Is Bitcoin Mining (5:11)
Source Files
Blockchain and Cryptocurrency Machine Learning - 01 What is Machine Learning
01 What Is Machine Learning (5:26)
02 What Is Supervised Learning (10:39)
Blockchain and Cryptocurrency Machine Learning - 03 Regression Machine Learning with Blockchain API
00A Project Preview (2:12)
00B What Is Linear Regression (5:03)
01 Collect Data From Blockchain Api (12:57)
02 Join CSV Files With Blockchain Data (9:01)
03 Process Data (4:06)
04 Visualize Data (11:19)
05 Create X And Y (6:15)
06 Build A Linear Regression Model (4:59)
07 Build A Polynomial Regression Model (5:53)
Source Files
Blockchain and Cryptocurrency Machine Learning - 04 Clustering Machine Learning on Cryptocurrencies
00A Project Preview (3:02)
00B What Is Unsupervised Learning (8:17)
01 Collect Crypto Data With Cryptocompare API (9:35)
02 Clean Data (8:10)
03 Process Text Features (7:26)
04A What Is Principal Component Analysis (7:27)
04B Reduce Data Dimensionality With Principal Component Analysis (4:41)
05A What Is K Means Clustering (11:58)
05B Cluster Cryptocurrencies With K-Means Clustering (7:41)
06 Machine Learning With Optimal Number Of Clusters (4:48)
07 Visualize Clusters (5:25)
Source Files
Blockchain and Cryptocurrency Machine Learning - 05a Build a K Nearest Neighbors Model
01 What Is K Nearest Neighbours (8:07)
02 Scrape Crypto Data With Yahoo Finance API (7:58)
03 Process Data (15:33)
04 Build A K-Nearest Neighbors Classifier (10:08)
05 Calculate Error For Different K Values (6:38)
Source Files
Blockchain and Cryptocurrency Machine Learning - 05b Build a Radius Neighbors Regression Model
00 What Is Radius Neighbors Machine Learning (5:03)
01 Load Stock Data With Yahoo Finance API (6:59)
02 Build X And Y Training And Testing Data (5:11)
03 Build A Radius Neighbors Regression Model (7:30)
Source Files
Blockchain and Cryptocurrency Machine Learning - 06a Build a CatBoost Model
00 What Is Catboost Machine Learning (2:26)
00B What Is Gradient Boosting (8:38)
01 Load Data (4:51)
02 Process Data (10:53)
03 Build A Catboost Classifier Model (7:31)
Source Files
Blockchain and Cryptocurrency Machine Learning - 06b Build an XGBoost Regression Model
00 What Is XGboost Machine Learning (1:31)
01 Load Stock Data With Yahoo Finance API (4:35)
02 Build An XGboost Regression Model (7:27)
Source Files
Blockchain and Cryptocurrency Machine Learning - 07a Neural Network Fundamentals
01 What Is Deep Learning (7:42)
02 What Is A Neural Network (8:47)
Blockchain and Cryptocurrency Machine Learning - 07b Build a Neural Network Classifier
01 Load Stock Data With Yahoo Finance API (7:20)
02 Build X And Y Training And Testing Data (6:13)
03 Build A Neural Network Classifier (6:29)
04 Calculate Neural Network Accuracy From Confusion Matrix (9:30)
Source Files
Blockchain and Cryptocurrency Machine Learning - 07c Build a Recurrent Neural Network with TensorFlow
00A Project Preview (2:12)
00B What Is A Recurrent Neural Network (6:38)
01 Load Stock Data With Yahoo Finance API (7:20)
02 Visualize Data (8:27)
03 Build A Training Dataset (8:04)
04 Build Features And Labels (10:37)
05 Build A Tensorflow Lstm Neural Network (12:04)
06 Load Test Data With An API (7:32)
07 Build Features And Labels For Testing The Neural Network (10:42)
08 Visualize Model's Predictions (8:42)
Source Files
Blockchain and Cryptocurrency Machine Learning - 08 Build a Bagging Classifier Model
00A Bagging And Decision Trees Introduction (5:25)
00B How Bagging Works (7:11)
01 Load Stock Data With Yahoo Finance API (8:34)
02 Build X And Y Training And Testing Data (6:00)
03 Train And Test A Bagging Classifier (7:34)
Source Files
Blockchain and Cryptocurrency Machine Learning - 09 Build a Light Gradient Boosted Regression Ensemble
00A Gradient Boosting Introduction (8:40)
00B What Is A Light Gradient Boosted Regression Ensemble (5:08)
01 Load Stock Data With Yahoo Finance API (5:08)
02 Build A Light GBM (7:59)
03 Find Best Number Of Trees (8:46)
04 Find Best Tree Depth (5:23)
Source Files
Blockchain and Cryptocurrency Machine Learning - 10 Build a Nested Cross Validation Model
00 What Is Nested Cross Validation (14:29)
01 Load Stock Data With Yahoo Finance Api (3:01)
02 Build More Features (6:32)
03 Define X And Y (5:55)
04 Implement Cross Validated Grid Search (6:02)
Source Files
Blockchain and Cryptocurrency Machine Learning - 11 Differential Privacy Project
00 What Is Differential Privacy (7:18)
01 Differential Privacy Project Introduction (13:16)
02 Build An Initial Database (3:05)
03 Build A Parallel Database (4:04)
04 Build Multiple Parallel Databases (3:09)
05 Determine If Query Leaks Private Data (5:12)
06 Calculate Sensitivity Of Mean Query (6:29)
07 Build Local Differential Privacy (9:09)
Source Files
Blockchain and Cryptocurrency Machine Learning - 12 Deep Learning Differential Privacy Project
00 Deep Learning Differential Privacy Introduction (13:22)
01 Build Database (3:45)
02 Build A Differential Privacy Query (4:10)
03 Perform Pate Analysis (6:10)
Source Files
Blockchain and Cryptocurrency Machine Learning - 13 Build a Federated Learning Model
00 What Is Federated Learning (6:28)
01 Generate A Dataset (10:03)
02 Build A Regular Model (7:43)
03 Visualize Model Results (7:01)
04 Build A Client-Side Model (2:51)
05 Build An Aggregator Model (2:07)
06 Generate Clients Dataset (9:26)
07 Execute The Federated Learning Model (9:58)
08 Evaluate The Model (3:36)
Source Files
LEVEL 6 - Data Science and Machine Learning - Python SQL Ethereum Data Science with Google BigQuery - Overview
Machine Learning Fundamentals (13:46)
Ethereum SQL (7:07)
Source Files
Python SQL Ethereum Data Science with Google BigQuery - 01 Google Cloud Platform and BigQuery
01 What Are Google Cloud Platform And Bigquery (6:01)
02 Build A Project On Google Cloud Platform (4:26)
Python SQL Ethereum Data Science with Google BigQuery - 02 SQL Introduction (Prerequisite)
01 Why You Must Know How To Work With Data-1 (5:22)
Source Files
02 SQL Introduction (Prerequisite) - 02 Entity Relationship Modeling (ERM)
01 How To Read An Er Model-1 (5:32)
Source Files
02 SQL Introduction (Prerequisite) - 03 Introduction to databases and relational databases
01 What Is A Database-1 (8:26)
02 What Is A Relational Database-2 (4:33)
Source Files
02 SQL Introduction (Prerequisite) - 04 How to build an organized database
01 How To Design Columns And Data Types-1 (3:13)
02 Use Normal Forms To Check Your Design-2 (7:16)
Source files
02 SQL Introduction (Prerequisite) - 05 Build a SQLite database with Python
01 Build A Sqlite Database With Python-1 (8:02)
02 Add An Entry To The Table With Sql-2 (6:44)
03 Add More Records To The Table-3 (6:30)
04 Build A Second Table For Cross-Referencing-4 (10:57)
05 Select Rows That Meet Conditions-5 (7:15)
Source files
Python SQL Ethereum Data Science with Google BigQuery - 05 Simple BigQuery Python SQL queries
01 Find Entries In Big Query Public Dataset (10:16)
02 Filter Entries By State Column (9:11)
Python SQL Ethereum Data Science with Google BigQuery - 06 Simple BigQuery Ethereum queries
01 Query Tables In Crypto Ethereum Big Query Public Dataset (4:45)
02 Select Ethereum Traces By Date (9:05)
03 Get Total Ether Supply Each Day (3:40)
04 Select Transactions By Address And Timestamp (10:13)
Python SQL Ethereum Data Science with Google BigQuery - 07 Calculate transaction ratios
01 Get Zero Transaction Ratio For Blockchain (10:56)
02 Get Zero Transaction Ratio For Smart Contracts (8:41)
Machine Learning Fundamentals - Overview
00 Course Overview - Machine Learning Fundamentals (13:46)
Source Files
Machine Learning Fundamentals - 01 (Prerequisite) Introduction to Machine Learning
00 Types Of Machine Learning Models (12:17)
01 How Does A Machine Learning Agent Learn (7:38)
02 What Is Inductive Learning (4:11)
Machine Learning Fundamentals - 02 (Prerequisite) Introduction to Python
00. Introduction (4:42)
01 What is Google Colab (4:24)
02 What If I Get Errors (2:39)
03 How Do I Terminate a Session (2:40)
Machine Learning Fundamentals - 03 Probability and Statistics for Machine Learning
01 Probability And Information Theory Overview (5:15)
02 Combinatorics For Probability (8:44)
03 Law Of Large Numbers (10:38)
04 Calculate Center Of Distribution (7:40)
Source Files
Machine Learning Fundamentals - 04 Distributions in Machine Learning
01 Uniform Distribution (5:25)
02 Gaussian Distribution (3:45)
03 Log-Normal Distribution (3:27)
04 Exponential Distribution (3:04)
05 Laplace Distribution (1:54)
06 Binomial Distribution (9:05)
07 Multinomial Distribution (3:59)
08 Poisson Distribution (4:21)
Source Files
Machine Learning Fundamentals - 05 Machine Learning Optimization
01 Calculate Error Of Machine Learning Model (8:44)
Source Files
Data Engineering and Machine Learning Masterclass - Overview
00 Course Overview (3:26)
Source Files - Course Overview
Data Engineering and Machine Learning Masterclass - More About Machine Learning
03 Performance Of A Machine Learning Algorithm (4:14)
04 Handle Noise In Data (5:22)
05 Powerful Tools With Machine Learning Libraries- (12:11)
Data Engineering and Machine Learning Masterclass - 03 Load, clean and encode data
01 Load And Clean A Public Dataset (8:55)
01B What Is One-Hot Encoding (10:02)
02 Build X And Y Data With One Hot Encoding (4:57)
03 Logistic Regression With One Hot Encoding (2:20)
Data Engineering and Machine Learning Masterclass - 04 Data engineering for machine learning
04 Scale And Encode Data With Scikit-Learn (3:47)
04.04 What Is Scaling Data (6:36)
05 Build, Train And Test A Machine Learning Model (4:37)
Data Engineering and Machine Learning Masterclass - 05 Build regression and discretizer models
01 Compare Decision Tree And Linear Regression Models (6:26)
01C What Is The Kbins Discretizer (4:54)
02 Bin Data With Kbins Discretizer (3:42)
03 Compare Binned Regression Models (3:39)
04 Build A Linear Regression Model On Stacked Data (3:20)
05A What Is K Means Clustering (11:58)
Data Engineering and Machine Learning Masterclass - 06 Data transformation and feature selection for ridge regression
01 Build Univariate Nonlinear Transformatio (1:55)
01 What Is Gaussian Probability Distribution- (2:31)
01B What Is Poisson Distribution (1:08)
02 Build X and Y Data With Poisson Distribution In Numpy (3:34)
02C What Is Logarithmic Data Transformation (2:34)
03 Build A Ridge Regression Model (3:41)
Data Science with Stocks, Excel and Machine Learning - 00 Welcome to the Course
00.00 Course Overview-1 (5:43)
00 Source Files
Data Science with Stocks, Excel and Machine Learning - 01 Project Track Stocks in Excel
01.00 What You'll Learn (2:01)
01.01 Pull In Stock Data (8:21)
01.02 Pull In More Stock Information (5:08)
01.03 Calculate Equity And Returns (11:56)
01.04 Calculate Selling Strategy (9:25)
01.05 Calculate Total Returns (4:28)
01 Source Files
Data Science with Stocks, Excel and Machine Learning - 02A Other Techniques of Stock Prediction in Excel
02.01 Pull Historical Stock Data-1 (2:31)
02.02 Predict Stocks With Moving Average-2 (9:34)
02.03 Visualize Accuracy-3 (3:48)
02.04 What Is Exponential Smoothing-4 (4:15)
02.05 Predict Stocks With Exponential Smoothing-5 (7:37)
02 Source Files
Data Science with Stocks, Excel and Machine Learning - 02B Linear Regression on Stock Data in Excel
02.00 What You'll Learn-1 (1:46)
02.01 Pull Historical Stock Data-2 (5:49)
02.02 What Is Linear Regression-3 (4:45)
02.03 Linear Regression On Stock Data In Excel-4 (8:04)
02.04 Check Accuracy Of Linear Regression (12:53)
02b Source Files
Data Science with Stocks, Excel and Machine Learning - 03A Machine Learning Project Introduction
03.00 What You'll Learn-1 (2:01)
03.01 Build Models On The Web-2 (5:05)
03.02 What Libraries Will We Use-3 (5:56)
Source Files
Data Science with Stocks, Excel and Machine Learning - 03B Your First Machine Learning Stock Prediction Project
03.01 Scrape Data Via Api-1 (16:42)
03.02 Define Variables-2 (11:36)
03.03 Split Dataset For Training And Testing-3 (7:33)
03.04 Build A Linear Regression Model-4 (9:16)
03.05 Predict Stock Prices-5 (10:14)
03.06 Calculate Model Accuracy-6 (14:17)
03.07 Predict To Buy Or To Sell-7 (7:23)
03 Source Files
Data Science with Stocks, Excel and Machine Learning - 04 Deep Learning Project for Stock Market Prediction
04.00 Recurrent Neural Networks-1 (6:23)
04.01 Import Stock Data-2 (9:19)
04.02 What Is Shaping Data-3 (5:18)
04.03 Shape Training And Testing Data-4 (12:06)
04.04 What Is Scaling Data-5 (6:35)
04.05 Scale Data For Training-6 (11:24)
04.06 What Is Keras-7 (3:24)
04.07 Build A Keras Model-8 (14:03)
04.08 Scale And Shape Data For Testing-9 (5:33)
04.09 Test The Model-10 (5:15)
04 Source Files
Quiz - Test your knowledge
Quiz - Test your knowledge
3.3 Calculate minimums, maximums and averages from data sets
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