Data science courses in Orange: Visualize, Analyze, and Build Models Without Coding

Step into the world of data science using Orange, a no-code platform designed to simplify data exploration and machine learning. In this course, you’ll start by learning how to prepare and clean your datasets, transforming raw data into a structured format ready for analysis. With Orange’s intuitive drag-and-drop interface, you’ll perform data preprocessing with ease, managing missing data and applying transformations with just a few clicks.

Next, you’ll explore your data through Exploratory Data Analysis (EDA). Orange offers powerful visualization tools like scatter plots, box plots, and heatmaps, allowing you to investigate patterns, trends, and relationships hidden in your data. These visual insights are key to understanding the story your data tells, and Orange makes the process simple and engaging.

The course culminates with machine learning, where you’ll learn to build and evaluate models for tasks like classification, regression, and clustering. Orange’s visual workflow makes experimenting with algorithms easy, so you can train models, adjust parameters, and assess performance without writing a single line of code. By the end of the course, you’ll have the skills to apply data science techniques to real-world problems, making data-driven decisions confidently using Orange’s no-code environment.

https://iimskills.com/data-science-courses-in-orange/

1. DATA SCIENCE
COURSES IN
ORANGE
By IIMskills

2. INTRODUCTION
Orange is a visual, no-code data
science platform designed for users
at all levels, from beginners to data
professionals.
Provides an easy-to-use drag-and-
drop interface for working with data,
performing analysis, and building
machine learning models.
A great tool for those who want to
learn data science without the
complexity of programming
languages like Python or R.

3. COURSE OVERVIEW
Data Preparation: Techniques for cleaning, transforming, and
preprocessing data.
Exploratory Data Analysis (EDA): How to explore data using
visualizations to find patterns, trends, and correlations.
Machine Learning: Build and evaluate models for classification,
regression, and clustering without writing any code.

4. MODULE 1:
DATA PRESENTATION
FWhy Data Preparation Matters: Clean, well-structured data is the
foundation of accurate analysis and reliable models.
Techniques You’ll Learn:
Handling Missing Data: Fill in or remove missing values efficiently.
Data Transformation: Scale and normalize data to prepare for analysis
or modeling.
Feature Engineering: Create new features and transform existing ones to
enhance your dataset’s quality.

5. MODULE 2:
EXPLORATORY DATA ANALYSIS
MODULE 3:
MACHINE LEARNING
Why EDA is Important: Helps you
understand your data’s structure,
relationships, and trends before
applying any machine learning
models.
Why Machine Learning Matters: Leverage
algorithms to make predictions, classify
data, or find hidden clusters in large
datasets.

6. WHY ORANGE IS IDEAL FOR NO-CODE
LEARNING?
No-Code: No programming
knowledge needed, making it
accessible to a broader audience.
Visual Learning: Data science
concepts become easier to
understand with visual workflows
and interactive widgets.
Quick Iteration: Modify, test, and
evaluate different workflows or
models easily in a visual, flexible
environment.

7. COURSE
SUMMARY
Learn how to prepare and clean
data usingOrange’s no-code
interface.
Explore your data through
various visualizations to uncover
insights.
Build and evaluate machine
learning models like
classification, regression, and
clustering—all without writing a
line of code.

8. WEBSITE
https://iimskills.com/data-science-
courses-in-orange/bit of b