Autoplay
Autocomplete
Previous Lesson
Complete and Continue
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 Prepare Raw Data for Dashboard
Lesson content will be unlocked within 30 minutes.
Teachable is working on this bug.
No further action will be required on your part
.
Thank you for your patience