The Complete Python Automation and Machine Learning Bundle
Learn to code in Python! Save time and money to advance your career. Learn web scraping, machine learning, data science, Web3, Blockchain
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Do you want to get into the technology industry?
Do you want to master a hot new skill like automation?
Then our newest bundle is perfect for you!
This is our newest most in-depth e-learning bundle yet!
- Does coding stress you out? 😬
- Are you scared of looking for a new job?
- Do you think you're not smart enough? 🥴
- Are you worried you're not learning the right things?
- Are you overwhelmed by trying to learn on your own? 😨
- Do you want to learn faster?
Python for Automation eBundle
✅ No programming experience needed - We'll teach you everything you need to know
✅ Any computer with access to the internet. A Mac is required only for Xcode
✅ No paid software required
✅ We'll walk you through, step-by-step how to get all the software installed and set up
Level 1 - Python fundamentals for automation
Learn to code in one of the top 3 most hireable languages of the decade (and the #1 language for automation.)
No math or programming experience necessary.
- Learn how to code in Python.
- Build and run your first Python projects.
- Think like a Python developer.
Automate routine tasks like:
- Rename bulk files
- Merge Excel files
- Search text files
- Posting to social media
- And much more
Level 2 - Regular expressions
Learn to search for patterns in datasets and find what you need fast. A must-have skill for an IT professional or a data scientist today.
Once you learn the basic technique, you can apply your knowledge of regex to any programming language like Java, Python, JavaScript, Linux command line, etc.
- Find text in files and datasets
- Web scrape for data
- And more
Level 3 - Web scraping
- Learn automated web data extraction with Python, Beautiful Soup, and Selenium.
- Clean and modify your data with data mining.
- Automate your Excel datasets with OpenPyXL and Excel VBA.
Why?
- Save huge amounts of time and resources
- Use for automation, data science and machine learning
Courses include:
- Scrape the Web - Python and Beautiful Soup Bootcamp
- Web Automation with Selenium Python
- Data Mining with Python! Real-Life Data Science Exercises
- Automate Excel Files with Python OpenPyXL
- Beginners Excel VBA
- Intermediate Excel VBA
Level 4 - Machine learning automation
Learn how to use popular Python libraries:
- NumPy - fundamental package for scientific computing in Python
- Matplotlib's Pyplot - data visualization with plots, graphs and charts
- Pandas - fast, powerful, flexible and easy to use data analysis and manipulation tool
Learn machine learning and artificial intelligence from scratch.
- Learn how machine learning can solve problems in all disciplines.
- Learn how to build a machine learning program.
Courses include:
- Introduction to Machine Learning and Python Data Science
- Build Machine Learning Models
- Data Science with Stocks, Excel and Machine Learning
- Build Neural Networks
- Computer Vision and Deep Learning with OpenCV and Python - Build 15 Projects
- Text to Speech with Python Machine Learning, Deep Learning and Neural Networks
- Beginner to Advanced JavaScript
- Beginners Machine Learning Masterclass with Tensorflow.js
- Much more
Level 5 - IoT Automation
Learn Internet of Things automation of Google Assistant and Apple Home.
Part 1 - Google Assistant
- Learn how Google Assistant and Smart Home work.
- Learn JavaScript to build a web app to control your appliances.
- Manage events with Google's Firebase storage and deployment.
Part 2 - Apple HomeKit
- Learn to code in Swift and Xcode for the Apple App Store.
- Connect to HomeKit in your iOS app.
- Build homes and accessories in your app.
A Mac computer or MacOS virtual machine is required to use Xcode.
Bonus - Web3 Blockchain Automation!
Dive into the hottest new tool revolutionizing the financial industry, the Internet and starting a new era. Blockchain isn't just a headline. It's a set of automation and efficiency tools. If you don't learn Blockchain, you will get left-behind.
- Introduction to Blockchain
- Beginners Solidity for Ethereum Blockchain Masterclass
- Web3.py Blockchain Automation
- NFT and Smart Contract Development with Brownie.py
- Web 3.0 Programming Masterclass - Decentralized Application (Dapp) Development
- NFT Blockchain Decentralized App Development with Solidity & JavaScript
- Beginners Marlowe Haskell for Cardano Blockchain Masterclass
- And more
Requirements
- No programming or machine learning experience needed - We'll teach you everything you need to know.
- A Mac, PC or Linux computer.
- MacOs required for Apple Home Automation section only
We'll walk you through, step-by-step how to get all the software installed and set up.
Welcome to The Complete Python Automation and Machine Learning Bundle, the only course you need to learn automation. With over 50,000 reviews, our courses are some of the HIGHEST RATED courses online!
This masterclass is without a doubt the most comprehensive course available anywhere online. Even if you have zero experience, this course will take you from beginner to professional.
Here's why:
- This course is taught by 3 instructors with decades of programming experience.
- We've taught over 1 million students how to code and many have gone on to become professional developers or start their own tech startup.
- You'll save $72,000, the average cost of 6 coding bootcamps. You'll learn completely online at your own pace. You'll get lifetime access to content that never expires.
- The course has been updated to be 2022 ready. You'll learn the latest tools and technologies used at large companies such as Google, Apple and Amazon.
We'll take you step-by-step through engaging video tutorials and teach you everything you need to know to succeed as an automation programmer, machine learning specialist or software developer.
The course includes 1080p HD video tutorials and builds your knowledge while making real-world projects.
Testimonials
Frequently Asked Questions
How do I obtain a certificate?
Each certificate in this bundle is only awarded after you have completed every lecture of the course.
Many of our students post their Mammoth Interactive certifications on LinkedIn. Not only that, but you will have projects to show employers on top of the certification.
Is this an eBook or videos?
The majority of this course bundle will be video tutorials (screencasts of practical coding projects step by step.) We will also have several PDFs and all source code.
Can't I just learn via Google or YouTube?
This course is much more streamlined and efficient than learning via Google or YouTube. We have curated a massive 5-course curriculum to take you from absolute beginner to starting a high-paying career in AWS Machine Learning.
How will I practice to ensure I'm learning?
With each section there will be a project, so if you can build the project along with us you are succeeding. There is also a challenge at the end of each section that you can take on to add more features to the project and advance the project in your own time.
Read more FAQs in the FAQ tab.
About Mammoth Interactive
Mammoth Interactive's mission is to close the tech skills gap by providing affordable and accessible courses primarily targeting beginners. Our instructors make video tutorials that are practical and to the point. Learning at Mammoth Interactive will be the next step to improving your career and your life.
Unlock Your Completion Certificate
Upon completing each course in this bundle, you'll receive a Completion Certificate. You can feature this certificate on your resume and LinkedIn.
Your Instructor
Alexandra Kropf is Mammoth Interactive's CLO and a software developer with extensive experience in full-stack web development, app development and game development. She has helped produce courses for Mammoth Interactive since 2016, including the Coding Interview series in Java, JavaScript, C++, C#, Python and Swift.
Mammoth Interactive is a leading online course provider in everything from learning to code to becoming a YouTube star. Mammoth Interactive courses have been featured on Harvard’s edX, Business Insider and more.
Over 12 years, Mammoth Interactive has built a global student community with 4 million courses sold. Mammoth Interactive has released over 350 courses and 3,500 hours of video content.
Founder and CEO John Bura has been programming since 1997 and teaching
since 2002. John has created top-selling applications for iOS, Xbox and
more. John also runs SaaS company Devonian Apps, building
efficiency-minded software for technology workers like you.
Course Curriculum
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Start02. Variables (19:34)
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Start03. Type Conversion Examples (10:21)
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Start04. Operators (7:21)
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Start05. Operators Examples (22:09)
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Start06. Collections (8:39)
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Start07. Lists (11:55)
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Start08. Multidimensional List Examples (8:22)
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Start09. Tuples Examples (8:51)
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Start10. Dictionaries Examples (14:41)
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Start11. Ranges Examples (8:46)
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Start12. Conditionals (6:58)
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Start13. If Statement Examples (10:32)
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Start14. If Statement Variants Examples (11:35)
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Start15. Loops (7:17)
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Start16. While Loops Examples (11:47)
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Start17. For Loops Examples (11:35)
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Start18. Functions (8:04)
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Start19. Functions Examples (9:33)
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Start20. Parameters And Return Values Examples (14:08)
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Start21. Classes and Objects (11:30)
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Start22. Classes Example (13:28)
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Start23. Objects Examples (10:10)
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Start24. Inheritance Examples (17:43)
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Start25. Static Members Example (11:20)
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Start26. Summary and Outro (4:23)
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StartPython_Language_Basics
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StartIntro to Python Slides
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Start01 Find Words Of Specific Length Starting With Specific Letter (8:17)
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Start02 Find Expression Containing Numbers And Symbols In A Specific Format (4:23)
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Start03 Find Expression Of A Specific Format (5:10)
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Start04 Search Ignoring Capitalization (1:19)
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Start05 Find Words At Beginning Or End Of Line (3:45)
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Start06 Find Independent Words (2:34)
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StartSource Files
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Start00. Intro To Course And Python (9:57)
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Start01. Variables (19:19)
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Start02. Type Conversion Examples (10:06)
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Start03. Operators (28:54)
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Start04. Collections (8:24)
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Start05. List Examples (19:41)
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Start06. Tuples Examples (8:36)
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Start07. Dictionaries Examples (14:26)
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Start08. Ranges Examples (8:32)
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Start09. Conditionals (6:43)
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Start10. If Statement Examples (21:32)
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Start11. Loops (29:42)
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Start12. Functions (17:01)
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Start13. Parameters And Return Values Examples (13:54)
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Start14. Classes And Objects (34:11)
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Start15. Inheritance Examples (17:29)
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Start16. Static Members Examples (11:05)
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Start17. Summary And Outro (4:08)
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StartSource Files
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Start02 Build An Html Webpage To Scrape (12:42)
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Start03 Select Data Structures From A Webpage (5:48)
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Start04 Extract Urls And Text (5:24)
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Start05 Work With Tags (8:06)
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Start06 Work With Attributes (5:18)
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Start07 Add Navigation To A String (5:29)
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Start08 Navigate Html Contents (7:16)
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Start09 Find All Filter (4:51)
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StartSource Files
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Start01.01 Find Elements By Name (14:50)
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Start01.02 Find Elements By Id (7:34)
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Start01.03 Find Elements By Xpath (12:29)
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Start01.04 Find Input Field By Xpath (13:44)
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Start01.05 Find Elements By CSS Selector (9:14)
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Start01.06 Find Elements By Link Text (7:47)
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Start01.07 Find Elements By Partial Link Text (8:05)
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Start01.08 Find Elements By Classname (6:22)
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Start01.09 Find Elements By Tagname (7:29)
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StartSource Files
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Start02.01 Make a Workbook (11:01)
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Start02.02 Save a Workbook (3:51)
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Start02.03 Read a Workbook (8:02)
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Start02.04 Work with Rows and Columns (8:07)
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Start02.05 Use a Formula (8:41)
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Start02.06 Use Dates (7:18)
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Start02.07 Merge and Unmerge Cells (7:11)
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Start02.08 Fold a Range (6:17)
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Start02.09 Make a New Sheet (3:17)
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Start02.10 Copy Data to a Sheet (4:35)
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Start02.11 Remove a Sheet (3:45)
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Start02 Source Files
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Start04.00 Topics Overview (1:30)
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Start04.01 Object Hierarchymp4 (5:10)
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Start04.02 Change Multiple Worksheets (7:05)
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Start04.03 Add And Count Worksheets (6:01)
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Start04.04 Get Path Of A Workbook (5:14)
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Start04.05 Open And Close Workbooks (8:41)
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Start04.06 Loop Through Worksheets And Workbooks (8:19)
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Start04.07 Build A Sales Calculator (11:53)
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Start04.08 Change Charts (10:30)
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Start04 Source Files
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Start05.00 Topics Overview (1:22)
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Start05.01 Program A Range Of A Spreadsheet (6:55)
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Start05.02 Use Cells Instead Of A Range (6:04)
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Start05.03 Use A Range Variable (6:04)
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Start05.04 Select A Range (4:52)
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Start05.05 Access A Row (4:35)
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Start05.06 Copy And Paste A Range (8:45)
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Start05.07 Clear A Range (3:59)
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Start05.08 Count A Range (4:21)
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Start05 Source Files
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Start06.00 Topics Overview (1:03)
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Start06.01 Find The Current Region Of A Cell (7:23)
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Start06.02 Dynamic Range Program (7:11)
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Start06.03 Resize A Range (2:30)
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Start06.04 Select Entire Rows And Columns (6:33)
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Start06.05 Offset Property (3:32)
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Start06.06 End Property (5:06)
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Start06 Source Files
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Start07.00 Topics Overview (1:21)
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Start07.01 Union And Intersect Of Ranges (4:24)
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Start07.02 Detect Content (5:37)
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Start07.03 Build A Range Program (5:47)
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Start07.04 Change Text Color (4:30)
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Start07.05 Bold A Range (2:39)
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Start07.06 Change Cell Color (5:04)
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Start07.07 Work With Areas (4:55)
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Start07.08 Find Differences In Ranges (8:17)
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Start07 Source Files
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Start11.00 Topics Overview (1:58)
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Start11.01 Select Case (5:42)
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Start11.02 Build A Commission Calculator Project (6:11)
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Start11.03 Find Remainder With Mod (3:11)
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Start11.04 Check Number Program (6:38)
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Start11.05 K Smallest Value Program (6:54)
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Start11.06 Group By Font Style (6:45)
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Start11.07 Remove Empty Cells (5:26)
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Start11 Source Files
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Start13.00 Topics Overview (1:40)
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Start13.01 Loop Through Defined Range (3:37)
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Start13.02 Loop Through Entire Column (3:29)
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Start13.03 Do Until Loop (3:22)
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Start13.04 Use Step To Increment (4:22)
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Start13.05 Build A Pattern Project (4:49)
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Start13.06 How To Sort (5:32)
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Start13.07 Sort By Related Data (8:15)
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Start13.08 Delete Duplicate Values (6:10)
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StartSource Files
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Start14.00 Topics Overview (1:28)
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Start14.01 Join Strings (3:13)
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Start14.02 Extract Substrings From Left Or Right (3:07)
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Start14.03 Extract Substring At Middle (4:12)
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Start14.04 Get Length Of A String (2:40)
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Start14.05 Get Substring Position (3:16)
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Start14.06 How To Split Strings (4:56)
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Start14.07 Reverse Characters (4:10)
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Start14.08 Change String Casing (3:28)
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Start14.09 Count Words In A Range (8:17)
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StartSource Files
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Start16.00 Topics Overview (1:18)
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Start16.01 One Dimensional Array (5:46)
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Start16.02 Two Dimensional Array (6:25)
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Start16.03 Change Array Size (4:54)
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Start16.04 Build An Array (5:09)
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Start16.05 Populate Row With Array (3:21)
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Start16.06 Array Length (6:47)
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Start16.07 Split String Into An Array (4:28)
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Start16.08 Join Array Into A String (3:49)
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StartSource Files
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Start18.00 Topics Overview (1:36)
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Start18.01 How To Access Excel Functions (4:28)
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Start18.02 Disable Screen Updating (3:19)
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Start18.03 Disable Alerts (3:38)
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Start18.04 Show Progress Of Macro_1 (6:35)
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Start18.05 Read Data From A File (6:35)
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Start18.06 Write Data To A File (5:10)
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Start18 Source Files
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Start00. Course Intro (5:11)
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Start01. Intro to Numpy (6:20)
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Start02. Installing Numpy (3:59)
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Start03. Creating Numpy Arrays (16:55)
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Start04. Creating Numpy Matrices (11:57)
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Start05. Getting and Setting Numpy Elements (16:59)
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Start06. Arithmetic Operations on Numpy Arrays (11:56)
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Start07. Numpy Functions Part 1 (19:13)
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Start08. Numpy Functions Part 2 (12:36)
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Start09. Summary and Outro (3:01)
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StartSource Files
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Start00. Course Intro (5:30)
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Start01. Intro to Pyplot (5:10)
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Start02. Installing Matplotlib (5:51)
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Start03. Basic Line Plot (7:53)
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Start04. Customizing Graphs (10:47)
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Start05. Plotting Multiple Datasets (8:10)
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Start06. Bar Chart (6:26)
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Start07. Pie Chart (9:13)
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Start08. Histogram (10:14)
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Start09. 3D Plotting (6:28)
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Start10. Course Outro (4:09)
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StartPyplot Code
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Start00. Panda Course Introduction (5:43)
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Start01. Intro to Pandas (7:55)
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Start02. Installing Pandas (5:28)
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Start03. Creating Pandas Series (20:34)
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Start04. Date Ranges (11:29)
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Start05. Getting Elements from Series (19:20)
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Start06. Getting Properties of Series (13:04)
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Start07. Modifying Series (19:01)
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Start13. DataFrame Operations (20:09)
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Start08. Operations on Series (11:48)
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Start09. Creating Pandas DataFrames (22:57)
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Start10. Getting Elements from DataFrames (25:12)
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Start11. Getting Properties from DataFrames (17:44)
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Start12. Dataframe Modification (36:24)
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Start15. Reading CSVs (12:00)
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Start14 DataFrame Comparisons and Iteration (15:35)
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Start16. Summary and Outro (4:14)
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StartSource Files
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Start00. Course Intro.mp4 (6:04)
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Start01. Quick Intro to Machine Learning (9:00)
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Start02. Deep Dive into Machine Learning (6:01)
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Start03. Problems Solved with Machine Learning Part 1 (13:26)
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Start04. Problems Solved with Machine Learning Part 2 (16:25)
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Start05. Types of Machine Learning (10:15)
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Start06. How Machine Learning Works (11:40)
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Start07. Common Machine Learning Structures (13:51)
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Start08. Steps to Build a Machine Learning Program (16:34)
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Start09. Summary and Outro (2:49)
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StartIntro to Machine Learning Slides
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Start00. Course Intro (6:10)
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Start01. Intro to Tensorflow.mov (5:32)
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Start02. Installing Tensorflow (3:52)
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Start03. Intro to Linear Regression (9:26)
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Start04. Linear Regression Model - Creating Dataset (5:49)
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Start05. Linear Regression Model - Building the Model (7:22)
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Start06. Linear Regression Model - Creating a Loss Function (5:57)
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Start07. Linear Regression Model - Training the Model (12:42)
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Start08. Linear Regression Model - Testing the Model (5:22)
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Start09. Summary and Outro (2:55)
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StartSource Files
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Start00. Course Intro (6:57)
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Start01. Intro to Image Recognition (6:40)
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Start02. Intro to MNIST (4:42)
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Start03. Building a CNN Part 1 - Obtaining Data (15:40)
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Start04. Building a CNN Part 2 - Building the Model (10:14)
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Start05. Building a CNN Part 3 - Adding Loss and Optimizer Functions (4:57)
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Start06. Building a CNN Part 4 - Train and Test Functions (10:58)
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Start07. Building a CNN Part 5 - Train and Test the Model (9:17)
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Start08. MNIST Image Recognition with Keras Sequential Model (13:23)
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Start09. Summary and Outro (2:55)
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StartSource Files
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Start01 What Are Search Algorithms (7:20)
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Start02 Depth First Search (9:00)
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Start02b Build A Depth First Search Algorithm (8:26)
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Start03 What Is Breadth First Search (bfs) (5:08)
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Start03b Build A Breadth First Search Algorithm (6:55)
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Start04 Depth Limited Search (3:57)
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Start05 Iterative Deepening Depth First Search (5:32)
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Start06 What Is Uniform Cost Search (6:04)
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Start06b Build A Uniform Cost Search Algorithm (8:07)
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Start07 Bidirectional Search (4:43)
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StartSource Files
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Start01 How Does A Machine Learning Agent Learn (7:37)
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Start02 What Is Inductive Learning (4:10)
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Start03 Make Decisions With Decision Trees (10:49)
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Start04 Performance Of A Machine Learning Algorithm (4:13)
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Start05 Handle Noise In Data (5:20)
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Start06 Statistical Learning (3:56)
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StartSource Files
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Start05.01 What Is Logistic Regression (4:26)
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Start05.02 Prepare Data For Logistic Regression (12:19)
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Start05.03 How To Prepare Data (8:52)
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Start05.04 Build A Logistic Regression Model (5:29)
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Start05.04a How To Build A Logistic Regression Model (3:28)
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Start05.04b What Is Optimization (12:10)
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Start05.05 Optimize The Logistic Regression Model (12:44)
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Start05.05a How To Optimize A Logistic Regression Model (12:45)
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Start05.06 Train The Model (10:09)
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Start05.07 Test The Model (2:33)
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Start05.08 Visualize Results (5:38)
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Start05 Source Files
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Start06.01 What Is Gradient Boosting (1:54)
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Start06.02 Prepare Data For Gradient Boosted Classification (7:19)
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Start06.03 Build Binary Classes (6:12)
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Start06.04a How To Shape Data For Classification (2:57)
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Start06.04b Shape Data For Classification (7:06)
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Start06.05a How To Build A Boosted Trees Classifier (4:03)
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Start06.05b Build A Boosted Trees Classifier (4:37)
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Start06 Source Files
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Start03.01 Scrape Data Via Api-1 (16:42)
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Start03.02 Define Variables-2 (11:36)
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Start03.03 Split Dataset For Training And Testing-3 (7:33)
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Start03.04 Build A Linear Regression Model-4 (9:16)
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Start03.05 Predict Stock Prices-5 (10:14)
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Start03.06 Calculate Model Accuracy-6 (14:17)
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Start03.07 Predict To Buy Or To Sell-7 (7:23)
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Start03 Source Files
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Start04.00 Recurrent Neural Networks-1 (6:23)
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Start04.01 Import Stock Data-2 (9:19)
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Start04.02 What Is Shaping Data-3 (5:18)
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Start04.03 Shape Training And Testing Data-4 (12:06)
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Start04.04 What Is Scaling Data-5 (6:35)
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Start04.05 Scale Data For Training-6 (11:24)
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Start04.06 What Is Keras-7 (3:24)
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Start04.07 Build A Keras Model-8 (14:03)
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Start04.08 Scale And Shape Data For Testing-9 (5:33)
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Start04.09 Test The Model-10 (5:15)
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Start04 Source Files
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Start09.01 What Is A Neural Network (8:02)
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Start09.02 Prepare Data (8:31)
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Start09.03 Shuffle And Batch Data (3:26)
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Start09.04 Build Weights And Biases (6:25)
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Start09.05 Build A Neural Network From Scratch (5:28)
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Start09.06 Optimize The Model (10:20)
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Start09.07 Train And Evaluate The Model (11:36)
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Start09.08 Test And Visualize The Neural Network (9:57)
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Start09 Source Files
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Start11.01 What Is A Convolutional Neural Network-1 (4:32)
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Start11.02 Prepare Data For A Convolutional Neural Network-2 (4:09)
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Start11.03 Shuffle And Batch Data-3 (2:17)
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Start11.04 Build Weights And Biases-4 (8:48)
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Start11.05 What Are Wrappers-5 (18:09)
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Start11.06 Build A Convolutional Neural Network From Scratch-6 (9:57)
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Start11.07 What Is The Adam Optimizer-7 (13:20)
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Start11.08 Train And Evaluate The Model-8 (10:32)
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Start11.09 Test And Visualize The Convolutional Neural Network-9 (7:49)
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Start11 Source Files
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Start13.01 What Is A Recurrent Neural Network-1 (4:58)
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Start13.02 Prepare Data For A Recurrent Neural Network-2 (7:25)
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Start13.03 Shuffle And Batch Data-3 (2:43)
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Start13.04 Build A Recurrent Neural Network-4 (7:42)
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Start13.05 Calculate Accuracy And Loss-5 (4:53)
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Start13.06 Optimize The Neural Network-6 (5:08)
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Start13.07 Train A Recurrent Neural Network-7 (6:09)
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Start13 Source Files
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Start14.01 What Is A Dynamic Neural Network (6:09)
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Start14.02 Generate Sample Data (13:39)
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Start14.03 Shuffle And Batch Data (4:23)
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Start14.04 Build A Dynamic Neural Network (7:34)
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Start14.05 Calculate Accuracy And Loss (5:15)
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Start14.06 Optimize The Neural Network (7:29)
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Start14.07 Train A Dynamic Neural Network (11:55)
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Start14 Source Files
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Start15.01 What Is A Bi-directional Neural Network (5:46)
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Start15.02 Prepare Data For A Bi-directional Neural Network (8:54)
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Start15.03 Build A Bi-directional Neural Network (8:43)
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Start15.04 Calculate Accuracy And Loss (5:51)
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Start15.05 Optimize The Bi-directional Rnn (5:29)
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Start15.06 Train A Recurrent Neural Network (6:44)
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Start15 Source Files
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Start00 How To Become A Web Developer (7:39)
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Start01 HTML Basics (7:26)
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Start02 CSS Basics (5:50)
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Start03 Add Images To Website With HTML (9:13)
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Start04 Link To Pages With HTML Hyperlinks (5:30)
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Start05 Positioning Items On A Webpage With CSS Flexbox (11:31)
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Start06 Spacing Out Items With Flexbox (9:31)
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Start01. Javascript Intro (10:40)
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Start02. Strings (5:50)
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Start03. Numbers (5:08)
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Start04. Booleans Intro (5:08)
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Start05. If Statements (4:43)
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Start06. Arrays (8:47)
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Start07. For Loops (9:32)
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Start08. While Loops (4:49)
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Start09. Objects (8:18)
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Start10. Functions (6:25)
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Start11. Foreach (4:09)
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Start12. Map Functions (5:37)
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Start13. Using Objects As Dictionary (3:01)
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Start14. Switch Statements (6:53)
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Start15. Destructuring (5:45)
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Start16. Spread Operator (7:12)
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Start17. String Templates (6:53)
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Start18. Error Handling (6:01)
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Start19. Let And Const Keywords (3:54)
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Start20. Do-while (2:01)
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Start21. Sets (5:57)
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Start22. Maps (4:55)
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Start23. Stacks (6:22)
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Start24. Queues (12:05)
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Start25. For Loop (5:27)
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Start26. Recursive Functions (7:29)
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Start27. Loop Labeling (5:34)
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Start28. 2d Arrays (22:15)
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Start29. Settimeout (7:18)
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Start30. Sentimental (11:37)
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Start31. Functions With Optional Parameters (15:26)
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Start32. Basic Regular Expression (6:09)
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Start33. Handle Keypress Events (23:01)
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Start34. Priority Queue (16:09)
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Start35. Adddelete Object Property (3:00)
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Start36A. Example With Sets (dropdowns) (11:10)
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Start36b. Example With Sets (add Button) (13:34)
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Start36c. Example With Sets (remove Button) (5:03)
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Start36d. Example With Sets (refactoring) (16:19)
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Start36e. Example With Sets (reduce Function) (14:04)
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Start36f. Example With Sets (debugging) (14:04)
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Start37. Concat (3:28)
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Start38. Flat And Flatmap (2:21)
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Start02 01 What Will We Learn In This Section (0:43)
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Start02 02 Declare Variables With Let And Const (16:05)
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Start02 03 Blocks And Iifes (11:49)
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Start02 04 Strings In Es2020 (11:48)
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Start02 05 Coding Challenge (0:52)
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Start02 06 Coding Challenge Solution (2:11)
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Start02 07 Section Summary (0:46)
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Start02. Source Files
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Start08 01 What Will We Learn In This Section (1:03)
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Start08 02 Asynchronous Javascript Example (11:20)
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Start08 03 The Event Loop (12:22)
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Start08 04 Asynchronous Javascript with Callbacks (9:25)
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Start08 05 Promises (21:18)
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Start08 06 Async Await (11:44)
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Start08 07 Ajax And Apis (6:41)
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Start08 08 Make Ajax Calls With Fetch And Promises (11:31)
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Start08 09 Make Ajax Calls With Fetch And Async Await (7:32)
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Start08 10 Coding Challenge (0:52)
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Start08 11 Coding Challenge Solution (7:41)
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Start08 12 Section Summary (0:57)
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Start08. Source Files
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Start01 Sync Intent - Define Appliance Metadata And Capabilities (4:25)
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Start02 Query Intent - Process List Of Target Devices (4:11)
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Start03 Query Intent - Get Current State Of Firebase And Appliance (3:13)
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Start04 Execute Intent - Update Appliance State (4:20)
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Start05 Execute Intent - Update Realtime Database (2:19)
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StartSource files
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Start00. Intro And Demo-1 (6:48)
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Start01. General Interface Intro-2 (15:06)
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Start02. File System Introduction-3 (13:24)
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Start03. Viewcontroller Intro-4 (6:53)
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Start04. Storyboard File Intro-5 (17:28)
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Start05. Connecting Outlets And Actions-6 (14:12)
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Start06. Running An Application-7 (10:06)
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Start07. Debugging An Application-8 (11:40)
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StartXCode Intro
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Start00. Language Basics Topics List (5:14)
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Start00. Learning Goals (4:24)
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Start01. Intro To Variables And Constants (16:16)
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Start02. Primitive Types (19:07)
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Start03. Strings (19:11)
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Start04. Nil Values (13:16)
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Start05. Tuples (14:39)
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Start06. Type Conversions (23:40)
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Start07. Assignment Operators (11:43)
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Start08. Conditional Operators (12:51)
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StartSource Code