Exploring Data with Python
Practical Skills for Real-World Data Challenges
Updated on Sep, 2025
Language - English
Development ,Data Science,Python
Lectures -9
Duration -2 hours
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Course Description
Welcome to our "Exploring Data with Python" course! This journey will take you through the fascinating world of data analysis, where we uncover valuable insights and patterns hidden within data. This course is meticulously designed to equip learners with essential skills and techniques required for effective data exploration and analysis.
In this course, you'll start with the basic exploration of python, one of the most popular programming languages in data science. We'll guide you through the essential skills and techniques required for effective data exploration. You’ll learn how to handle missing values and outliers, perform feature scaling, and create insightful data visualizations.
You'll engage in hands-on exercises that will help you apply your new skills. By analyzing different types of data, you will learn how to clean and pre-process data, perform exploratory data analysis, and visualize your findings to tell compelling stories. Whether you’re a student, professional developer, data scientist, aspiring AI engineer, enhance your current role or someone looking to start a career in data science, or simply gain a deeper understanding of data, this course will set you on the path to success. Start your journey to mastering Python with us and unlock limitless opportunities in programming and technology. Enroll today and elevate your skills to new heights!
Who this course is for:
- Aspiring Data Analysts
- Students and Academics
- Professionals in Various Industries
- Researchers and Scientists
- Freelancers and Entrepreneurs
- Career Changers
- Anyone Interested in Data Analysis
Goals
Data Interpretation: Master interpreting visualizations and summary statistics to derive meaningful insights from data.
Data Exploration Skills: Understanding Data Structures and Data Summarization
Data Cleaning and Preprocessing: Handling Missing Values, Outlier Detection, and applying appropriate techniques to improve data quality.
Data Visualization Proficiency: Visual Representation using Python libraries like Matplotlib and Seaborn.
Feature Scaling and Preprocessing: Implementing feature scaling techniques such as normalization and standardization to prepare data for machine learning model
Prerequisites
Fundamental computer skills and comfort with installing and using software.
Basic understanding of Python programming.
Essential math and statistics knowledge is helpful
Curriculum
Check out the detailed breakdown of what’s inside the course
Basic Exploration
1 Lectures
-
Basic Exploration
18:46
18:46
Dealing With Missing Values
1 Lectures
Dealing With Outliers
2 Lectures
Data Visualization
3 Lectures
Feature Scaling
2 Lectures
Instructor Details
GreyCampus Inc.
About me
GreyCampus helps people power their careers through skills and certifications. We believe continuous upskilling and certifications is key to sustained success in your career. While older skills are fast becoming less relevant, need for newer in-demand skills is growing exponentially. We believe if you stay skilled, you will stay ahead.
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