Advanced Data Analysis for Beginners, Orange Step-by-Step Master Pack

Name: Advanced Data Analysis for Beginners, Orange Step-by-Step Master Pack
Price: 293700 KRW
Rating: 5 (2 reviews)

Data analysis is complete with this one tool. Get started with Orange AI data analysis without coding!

(5.0) 2 reviews

21 learners

Level Beginner

Course period Unlimited

Masocampus

Orange3

No-code

Machine Learning(ML)

Statistics

Orange3

No-code

Machine Learning(ML)

Statistics

What you will gain after the course

How to use Orange, a no-code artificial intelligence data analysis tool
The entire data analysis process that uses real data to gain insights.
Why You Should Use Orange Among Various Data Analysis Tools
From data mining to preprocessing, supervised learning, and machine learning techniques

This one tool is all you need for data analysis. Get started with Orange AI data analysis without coding!

This one tool is all you need for data analysis.

Comprehensive data analysis tool!

With the more powerful Orange
Start analyzing data easily

Check the results yourself
Feel how powerful a tool it is

Orange, data analysis that sets you apart from others!

Orange lets even beginners see the data analysis process at a glance!
A variety of data skills that were not available with Excel alone

- Completely free! From the basics to the practical use of Orange
– Completely no-coding, Python-based
– Machine learning made easy and fast

Usher in a new era of data analytics with Orange 3.
Let AI help you derive data insights.

Course Experience Group Reviews
IT lectures created with expertise and know-how

Advanced data analysis starting from the basics

Easy data analysis even for beginners

I wanted to start data analysis, but Python and R were too difficult or required specialized coding knowledge, and ChatGPT always gave me the wrong answer, so I gave up.

But, I really enjoyed this course because it allowed me to learn tools that allow for easy data analysis and even advanced usage !

Experience Group Review (Lee**)

Completely no-coding, Python-based

I liked that I could quickly perform the analysis I wanted just by giving them the data.

I hesitated because I didn't know what to do even when I started coding.
It was based on Python and it was completely no-coding, so it was easier to get started !
The tool called Orange itself isn't difficult, so I plan to learn more analysis techniques :)

Experience Group Review (Po****)

Master all the steps at once

Although I was born and raised in the field of biology, as the world changes, data analysis and visualization seem to have become essential.

It's a field that I've given up on many times because it's difficult, but I was able to learn it without fear because it's so intuitive .
Above all, I think the best thing is that you can learn step by step, from installation to basic and advanced use .

Experience Group Review (Se*)

Orange Data Analysis Comprehensive Curriculum Features

This comprehensive course covers everything from the fundamentals of data analysis to advanced predictive modeling .

1. From basic to advanced
A systematic curriculum that includes data exploration, visualization, machine learning, text mining, and network analysis.

2. Efficient lectures that only cover the key points
Intensive and efficient core training that takes into account busy schedules

3. A comprehensive overview of the latest data analysis techniques.
The latest data analysis technology trends summarized in one lecture.

4. Becoming a Data Analysis Expert
Learn how to derive powerful insights without complex coding.

I confidently recommend this to these people.

– All office workers and managers who want to increase productivity through data analysis
– IT professionals who want to apply the latest data analysis techniques to their work.
– Managers and planners who want to understand and apply data-driven business strategies.
– Job seekers and students in fields requiring in-depth data visualization, such as finance and consulting

This course provides you with everything you need to grow into a data analytics professional.
Experience the revolution in data analysis with Orang e's powerful features and cutting-edge techniques.

Introducing the knowledge sharer

Lecture Features

STEP 1. Introduction to AI-Based Data Analysis

Learn how to use the no-coding artificial intelligence tool Orange and learn the basic concepts of machine learning data analysis.

STEP 2. Data Preprocessing and Visualization

Learn data cleansing and missing value handling, data transformation, encoding, and scaling techniques, and learn data visualization techniques.

STEP 3. Predictive Machine Learning Analysis

Strengthen practical application skills through hands-on practice of advanced analytical techniques, such as building and evaluating predictive models and acquiring optimization techniques.

STEP 4. Classification Machine Learning Analysis

Understanding and building various classification models, such as logistic regression, SVM, and random forests.

STEP 5. Advanced Data Analysis in Practice

Master machine learning-based data analysis skills by applying advanced techniques to real-world cases.

Expected Questions Q&A

Q. Do I need prior knowledge of artificial intelligence, coding, or design?
A. This course is designed to provide anyone interested in artificial intelligence with the skills they need to apply it in practice. It does not require any AI, coding, or even Excel skills.

Q. Are there any requirements or prerequisites for taking the course?
A. Since this is a practice-oriented lecture, it would be a good idea to prepare a dual monitor or extra device that can separate the lecture and practice screens.

Q. Orange? Do I need to purchase separate software?
A. Orange is distributed free of charge, and it provides step-by-step instructions, from download to installation, so anyone can easily build an AI data analysis environment. The portable version allows use without an external internet connection, making it ideal for use in high-security work environments.

Please check before taking the class!

Since this is a practice-oriented lecture, it would be a good idea to prepare a dual monitor or extra device that can separate the lecture screen and the practice screen.
Additionally, since the training is conducted based on Windows OS, we recommend taking the course in a Windows environment.

Recommended for
these people

Who is this course right for?

All workers and managers who want to increase productivity through data analysis
IT professionals who want to apply the latest data analysis techniques to their work
Managers and planners who want to understand and apply data-driven business strategies
Job seekers and students in fields that require data visualization, such as finance and consulting

Need to know before starting?

This course is designed to provide anyone interested in data analysis with the ability to immediately apply it in practice. It does not require AI, coding, or even Excel skills.

Hello
This is

9,420

Learners

1,337

Reviews

114

Answers

4.7

Rating

Courses

"I will grow more than yesterday. And, I will help those who strive to grow more than yesterday."

With Actionable Content that embodies the sincerity and aspirations of Maso Campus,

100 million cumulative hours of lectures shared online and offline since 2013!

This precious experience and time are always the source of growth for both Maso Campus and our students.

The Miso Campus team strictly adheres to two principles for the growth of us all. 1. Actionable Content that can be put into practice immediately after learning. 2. Respecting the time and effort of participants.

The Miso Campus team strictly adheres to two principles for the growth of us all.

1. Actionable Content that you can actually use after learning 2. Time-Saving Curriculum that respects the participant's time and effort Grow with Miso Campus's Actionable and Time-Saving Curriculum

1. Actionable Content that you can surely use once you learn it

2. Time-Saving Curriculum that respects the time and effort of participants

We hope you will walk the path of growth together with Masocampus's Actionable and Time-Saving Curriculum.

We hope you will walk the path of growth together with Maso Campus's Actionable and Time-Saving Curriculum.

Curriculum

All

136 lectures ∙ (43hr 24min)

Course Materials:

Lecture resources

Section 1. 1. No-Code AI Data Analysis Using Orange Lv.0: Introduction to AI-Based Data Analysis

1 lectures

1. AI Data Analysis without Coding Using Orange: Lv.0 Textbook

Section 2. 1-1. Course Introduction

1 lectures ∙ (1min)

2. [onc94] ORA0101 Course Introduction
01:09

Section 3. 1-2. Introduction to the No-Coding Analysis Tool Orange

5 lectures ∙ (42min)

3. [onc94] ORA0201 Understanding No-coding Analysis Tools
02:10
4. [onc94] ORA0202 Preparing the Orange analysis environment_Standalone version installation
06:01
5. [onc94] ORA0203 Preparing the Orange Analysis Environment - Installing the Portable Version
02:53
6. [onc94] ORA0204 Performing the World's Easiest Regression Analysis for Understanding Orange
17:43
7. [onc94] ORA0205 Using various datasets in Orange
13:36

Section 4. 1-3. Orange Data Analysis Introduction

2 lectures ∙ (34min)

Section 5. 1-4. Introduction to AI-based Data Analysis

4 lectures ∙ (1hr 24min)

Section 6. 1-5. AI-based data analysis summary

1 lectures ∙ (11min)

Section 7. 2. AI Data Analysis Without Coding Using Orange - Lv.1 First Steps in Data Mining

2 lectures

Section 8. 2-1. Guide to Learning Content

1 lectures ∙ (6min)

Section 9. 2-2. No-code data analysis tools: need and installation

3 lectures ∙ (48min)

Section 10. 2-3. Handling Data Analysis Workflow

2 lectures ∙ (41min)

Section 11. 2-4. Data Analysis Models and Machine Learning Algorithms: Supervised and Unsupervised Learning

5 lectures ∙ (1hr 34min)

Section 12. 2-5. Importing data from various sources

3 lectures ∙ (1hr 4min)

Section 13. 2-6. The Core of Algorithm Selection, Data Types and Roles

2 lectures ∙ (58min)

Section 14. 2-7. Data Sampling and Information Setting

3 lectures ∙ (1hr 40min)

Section 15. 2-8. Deriving Insights Using Descriptive Statistics

3 lectures ∙ (1hr 0min)

Section 16. 2-9. Confirmatory Data Analysis

1 lectures ∙ (33min)

Section 17. 2-10. No-Code Analysis and Reading Results of the 3 Most Common Major Analysis Methods

4 lectures ∙ (1hr 14min)

Section 18. 2-11. Smart Machines Replacing People

1 lectures ∙ (29min)

Section 19. 3. AI Data Analysis Without Coding Using Orange - Lv.2 Data Preprocessing and Visualization

2 lectures

Section 20. 3-1. Learning Content Guide

1 lectures ∙ (6min)

Section 21. 3-2. Feature Engineering Essentials

2 lectures ∙ (26min)

Section 22. 3-3. Data Cleansing

5 lectures ∙ (1hr 44min)

Section 23. 3-4. Handling Missing Values

2 lectures ∙ (40min)

Section 24. 3-5. Outlier Handling

2 lectures ∙ (45min)

Section 25. 3-6. Data Transformation and Encoding

3 lectures ∙ (1hr 9min)

Section 26. 3-7. Data Scaling

1 lectures ∙ (29min)

Section 27. 3-8. Data Preprocessing Pipeline and Sampling

3 lectures ∙ (56min)

Section 28. 3-9. Feature Creation with Grouping and Formulas

3 lectures ∙ (1hr 20min)

Section 29. 3-10. Effective visualization methods and grids

2 lectures ∙ (27min)

Section 30. 3-11. Visualization for Data Comparison and Analysis

5 lectures ∙ (1hr 8min)

Section 31. 3-12. Visualization for Understanding Data Relationships

6 lectures ∙ (56min)

Section 32. 3-13. Visualizing data distribution

3 lectures ∙ (42min)

Section 33. 3-14. Visualization for Data Structure Analysis

4 lectures ∙ (52min)

Section 34. 3-15. Map Visualization

1 lectures ∙ (11min)

Section 35. 4. No-Coding AI Data Analysis with Orange - Lv.3 Predictive Machine Learning Analysis

2 lectures

Section 36. 4-1. Learning Content Guide

1 lectures ∙ (3min)

Section 37. 4-2. What are Classification and Prediction

1 lectures ∙ (39min)

Section 38. 4-3. Understanding and Handling Prediction Models with Regression Analysis

4 lectures ∙ (1hr 31min)

Section 39. 4-4. A good model has accurate prediction results

4 lectures ∙ (2hr 2min)

Section 40. 4-5. A good model should be versatile

3 lectures ∙ (1hr 36min)

Section 41. 4-6. Good models are simple and not complex.

1 lectures ∙ (39min)

Section 42. 4-7. The Optimization Principle: The Top is Flat

3 lectures ∙ (1hr 24min)

Section 43. 4-8. Artificial Neural Network: AI's Core

5 lectures ∙ (1hr 55min)

Section 44. 5. Code-free AI Data Analysis using Orange - Lv.4 Classification Machine Learning Analysis

2 lectures

Section 45. 5-1. Binary classification dividing into two and calibration learning

3 lectures ∙ (1hr 12min)

Section 46. 5-2. How to Know if the Classification Was Done Well

6 lectures ∙ (2hr 25min)

Section 47. 5-3. Finding the Hyperplane in Support Vector Machines

2 lectures ∙ (46min)

Section 48. 5-4. KNN: Copying Your Neighbor When Unsure

1 lectures ∙ (33min)

Section 49. 5-5. Probability Multiplication of Two Independent Events and Naive Bayes

1 lectures ∙ (33min)

Section 50. 5-6. Tree and Random Forest, Classification Models Mimicking Trees and Forests

3 lectures ∙ (1hr 16min)

Section 51. 5-7. Building Custom Analysis Model from Data

1 lectures ∙ (21min)

Section 52. 5-8. Ensemble Method for Analyzing by Combining Multiple Models

4 lectures ∙ (1hr 17min)

Published:

Last updated:

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2 reviews

5.0

2 reviews

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Average Rating 5.0
5
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Advanced Data Analysis for Beginners, Orange Step-by-Step Master Pack

What you will gain after the course

📢 Please note before taking the class

This one tool is all you need for data analysis.

Comprehensive data analysis tool!

With the more powerful Orange Start analyzing data easily

Check the results yourself Feel how powerful a tool it is

Orange, data analysis that sets you apart from others!

Course Experience Group Reviews IT lectures created with expertise and know-how

Advanced data analysis starting from the basics

Easy data analysis even for beginners

Completely no-coding, Python-based

Master all the steps at once

Orange Data Analysis Comprehensive Curriculum Features

I confidently recommend this to these people.

Introducing the knowledge sharer

Lecture Features

Please check before taking the class!

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