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Free Download iOS Machine Learning with Core ML, Swift 6, and SwiftUI
Last updated 3/2026
MP4 | Video: h264, 1920×1080 | Audio: AAC, 44.1 KHz, 2 Ch
Language: English | Duration: 2h 14m | Size: 1.51 GB
Learn how to integrate machine learning into iOS apps. Hands-on Swift 6 coding using Core ML, Vision, CreateML and NLP.

What you’ll learn
Gain insights from a software engineer with over 30 years of hands-on professional experience.
Get a practical introduction to machine learning in iOS and macOS development.
Gain a practical understanding of Create ML, Core ML, Vision, and Natural Language Processing.
Train and evaluate custom image classifiers directly on your Mac using Create ML.
Set up and integrate Core ML models into SwiftUI projects.
Build iOS apps that can recognize objects, faces, barcodes, and text in photos and video streams.
Integrate natural language text analysis and sentiment detection into your apps.
The companion eBook (a $28.80 value on Amazon) is included free!
Requirements
To follow along, you’ll need a Mac running macOS Tahoe and Xcode 26, Apple’s latest development environment.
You should be comfortable with the basics of Swift 5 or Swift 6 programming – just enough to read and write simple code.
You should be familiar with Xcode basics such as creating projects and running apps.
Description
A practical, concise, and hands-on machine learning course you can complete in just a few hours – with a companion eBook included.
Wouldn’t it be great to add intelligent features like image recognition, natural language processing, or sentiment analysis to your iOS, macOS, or iPadOS apps?
In this course, you’ll learn how to unleash the power of machine learning using Core ML, Create ML, Vision, and Swift 6 with SwiftUI.
We’ll start by demystifying what machine learning is and how it works – explained in plain English, without jargon. We’ll explore Apple’s machine learning frameworks through real examples and hands-on Swift coding.
You’ll build practical iOS apps that can
• Recognize dog breeds from photos
• Analyze the sentiment of product reviews
• Detect faces, barcodes, and text in images using Vision
You’ll also learn how to train your own machine learning models right on your Mac using Create ML.
And there’s a lot more packed into this professional, focused course.
About the Instructor
I’ve been designing and building software for over 30 years for companies like Apple, Siemens, and SAP.
As a software architect, I helped create enterprise frameworks, including Siemens Healthcare’s syngo image processing system and Apple-SAP’s Cloud Platform SDK for iOS.
I currently hold twelve patents in the field of mobile computing.
What You’ll Learn
• How Apple’s machine learning frameworks fit together (Core ML, Create ML, Vision, NaturalLanguage)
• Natural language text processing and sentiment analysis
• Setting up and integrating Core ML models in Xcode projects
• Image recognition and object detection with the Vision framework
• Training and testing your own image classifiers on your Mac
Student Reviews
"Thank you Karoly, you’ve delivered another excellent course with detailed explanations and real-world examples that any app developer can put into practice."
– Jim McMillan
"The best introduction to Machine Learning with Swift – clear, practical, and beginner-friendly."
– Zbyszek Pietras
"Finally, a course that covers Core ML, natural language processing, and Create ML – exactly what I was looking for."
– Dan Gray
More Than an Online Course
• Personalized support: access to a private forum where I personally answer student questions
• Companion eBook: included with the course
• able demo projects: follow along and experiment with working examples
• Continuous updates: I keep the content current with the latest Apple tools and frameworks
30-Day Money-Back Guarantee
If you’re not completely satisfied, you’ll receive a full refund – no questions asked.
Go ahead and click Enroll. See you in the first lesson!
Who this course is for
Take this course to start building intelligent iOS apps with Create ML, Core ML, Vision, and Natural Language Processing.
This course is for you if you want to build smarter, more capable apps powered by machine learning.
Enroll if you’re interested in exploring the latest Apple technologies in the field of artificial intelligence.

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Introduction To Zbrush 2021
MP4 | ENG | Video: h264, yuv420p, 1920×1080 | Audio: aac, 48000 HZ | Duration: 40h:20m | Size File: 12.3 GB
Genre: eLearning​

Introduction to ZBrush 2021 is the most comprehensive video training series available for Pixologic’s industry-leading digital-sculpting software. Taught by Madeleine Scott-Spencer, this 65-chapter workshop – with 51 hours of lessons – begins with a quickstart tutorial to get you up to speed, fast. It’s the perfect introduction for everyone from complete beginners to those simply looking to see what’s new in the latest version of the software.

The first follow-along tutorial in this workshop tackles how to sculpt a character bust from a sphere while teaching the core ZBrush concepts, such as DynaMesh and how to effectively use subdivision levels, as well as demystifying the ZBrush interface and navigation. Subsequent chapters delve further into a more in-depth look at the ZBrush interface, including how to customize the interface and hotkeys, what are the important sculpting tools and techniques, plus explanations of 3D alphas, custom brushes, the InsertMultiMesh brush, Array Mesh functionality, the NanoMesh system, Vector Displacement brushes – plus much, much more.

All the exciting new features in ZBrush 2021 are, of course, covered including cloth, dynamic thickness, ZModeler updates such as Edge Extrude, and the new MicroPoly tools. Madeleine also discusses how to approach hard-surface sculpting in ZBrush plus how to use the polygon modeling tools such as ZModeler, the Topology brush, and ZRemesher. 3D Printing enthusiasts will also be pleased to discover a chapter devoted to the process of preparing a model for 3D printing using the Decimation Master plugin.

In addition to exploring all of ZBrush’s impressive sculpting tools, this workshop also covers its robust 3D painting program. Madeleine walks through PolyPaint, UV Master, and Spotlight, through detailed demonstrations of paint techniques drawing from more than 20 years of experience working in the film industry. Lighting and rendering chapters also take you through the process of generating final images using LightCaps and HDR images, as well as how to render through the ZBrush to KeyShot Bridge. Plus, Madeleine details the ZBrush Material menu and how to extract maps such as Displacement, Normal, and Color, as used in many film, TV, and videogame art pipelines.

To help with your understanding of this workshop, Madeleine provides helpful project files for you to download and follow along with most chapters. By completing this workshop, you should have the confidence to tackle your own projects as an intermediate-level ZBrush artist.

Introduction to the Splunk Ecosystem
Duration: 1h 5m | .MP4 1280×720 30 fps(r) | AAC, 48000 Hz, 2ch | 192.34 MB
Genre: eLearning | Language: English​

Understanding how data flows through Splunk is key to effective analysis. This course will teach you how to navigate the data pipeline, apply metadata, and perform efficient searches to uncover actionable insights.

More Info:
Introduction to the Splunk Ecosystem

Free Download Introduction to Multivariable Calculus 2026
Published 4/2026
Created by Renngang Engineering
MP4 | Video: h264, 1920×1080 | Audio: AAC, 44.1 KHz, 2 Ch
Level: Beginner | Genre: eLearning | Language: English | Duration: 6 Lectures ( 1h 36m ) | Size: 480 MB

Learn math from the best Scandinavian Instructors with Renngang Engineering
What you’ll learn
✓ Learn what multivariable analysis
✓ Learn what partial derivatives are
✓ Practice through solving real exam problems from top universities
✓ Instructor led guidance through every problem
Requirements
● No prior math knowledge is strictly speaking needed, but some prior engineering mathematics is beneficial
Description
Welcome to Multivariable Calculus 2026, a carefully designed introductory course created by Scandinavian instructors from Renngang Engineering, a Norwegian education initiative dedicated to clarity, rigor, and practical understanding.
This course is built for students who have completed single variable calculus and are ready to take the next step into higher dimensional thinking.
You will explore how calculus extends beyond one dimension, learning how to work with functions of multiple variables, visualize surfaces, and understand how change behaves in higher dimensions. Throughout the course, we emphasize geometric intuition, real world interpretation, and problemsolving skills.
What we will go through in the course
Understanding and analyzing multivariable functions
Interpreting and computing partial derivatives
Working with gradients, directional derivatives, and optimization techniques
Solve a lot of problems together
Why use us for your math understanding?
At Renngang Engineering, we believe mathematics should be both precise and understandable. Our approach avoids unnecessary complexity while maintaining academic depth, helping you build strong intuition alongside technical skill. Whether you’re an engineering student, a future scientist, or simply curious about advanced mathematics, this course provides a solid and inspiring foundation.
Join us and discover how multivariable calculus can be easy as long as you stick with us on the entire journey.
Who this course is for
■ Engineers and students
Homepage
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https://www.udemy.com/course/introduction-to-multivariable-calculus-2026

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Introduction to DeepSeek
.MP4, AVC, 1280×720, 30 fps | English, AAC, 2 Ch | 41m | 85.8 MB
Instructor: Ervis Trupja​

Understanding DeepSeek’s capabilities can be complex. This course will teach you to effectively evaluate, deploy, and optimize DeepSeek models for real-world AI applications through hands-on implementation.

What you’ll learn

DeepSeek’s open-source models are revolutionizing AI accessibility, but understanding their architecture and implementation can be challenging. In this course, Introduction to DeepSeek, you’ll learn to effectively evaluate and deploy these powerful models for real-world applications.

First, you’ll explore the innovative Mixture-of-Experts architecture that makes DeepSeek efficient, understanding how only 37B parameters are active during inference despite the model’s 671B total parameters. Next, you’ll discover how DeepSeek-R1’s reasoning capabilities compare against proprietary models through comprehensive benchmark analysis and practical demonstrations. Finally, you’ll learn how to implement DeepSeek models in production environments and calculate the total cost of ownership for different deployment strategies.

When you’re finished with this course, you’ll have the skills and knowledge of DeepSeek’s capabilities and limitations needed to make informed decisions about integrating these models into your AI workflow and applications.

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Introduction to Data Modeling with LookML
.MP4, AVC, 1920×1080, 30 fps | English, AAC, 2 Ch | 1h 17m | 204 MB
Instructor: Dr. Ali Feizollah​

Analysts working in Looker often hit a wall when metrics look wrong, fields go missing, or dashboards behave unexpectedly-issues that originate in the data model, not the query.

In this course, Introduction to Data Modeling with LookML, you’ll gain the ability to understand, build, and troubleshoot the LookML layer that powers every Explore.

First, you’ll explore what LookML is, how it fits into the Looker ecosystem, and how modeling decisions directly affect analyst workflows.

Next, you’ll discover how to model Explore joins that combine datasets safely while preserving metric accuracy. Then, you’ll see how to create dimensions for common analysis needs, including time-based fields and segmentation buckets.

Finally, you’ll learn how to create reliable, reusable measures with proper formatting, filters, and testing. When you’re finished with this course, you’ll have the skills and knowledge of LookML data modeling needed to read and modify a Looker data model, diagnose common data issues, and contribute meaningfully to your organization’s analytics layer.

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Introduction to Context Engineering
.MP4, AVC, 1280×720, 30 fps | English, AAC, 2 Ch | 1h 7m | 225 MB
Instructor: George Smith​

Level up in AI development by mastering how to structure, manage, and automate context that powers Large Language Models. Learn core concepts and technologies behind context engineering to build new transformative experiences with AI agents.

What you’ll learn

Many AI engineers know how to prompt Large Language Models but struggle to design and manage the context that makes those prompts truly effective. In this course, Introduction to Context Engineering, you’ll learn to structure, automate, and optimize the flow of information that powers AI models.

First, you’ll explore what context engineering is and why it matters. Next, you’ll discover the driving factors behind context design, like constraints. Finally, you’ll learn how to apply common context engineering patterns.

When you’re finished with this course, you’ll have the skills and knowledge of leveraging context engineering needed to build transformative AI experiences by effectively managing model context.

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