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Python for Data Analytics & Science

Name: Python for Data Analytics &amp; Science
Author: Baturi

Python for Data Analytics & Science

Download this premium online course featuring high-quality video training, step-by-step lessons, practical demonstrations, and expert instruction. With Python for Data Analytics & Science, you'll gain practical knowledge through structured learning, hands-on examples, and real-world applications. This comprehensive eLearning resource is ideal for students, professionals, freelancers, and lifelong learners looking to develop valuable skills and stay current with modern industry practices at their own pace.
Published 9/2026
Created by Indian Paradise Trainer
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch
Level: All Levels | Genre: eLearning | Language: English | Duration: 10 Lectures ( 2h 8m ) | Size: 869 MB

Learn Python, NumPy, Pandas, Data Visualization, EDA and real-world data analysis techniques from scratch

What you'll learn

⚡ Python for Data Analytics
⚡ Numpy Fandamentals
⚡ Numpy Analytics
⚡ Pandas Fundamentals
⚡ Python for Data Science

Requirements

❗ Very Basic Coding Idea

Description

Are you looking to learn Python for Data Analytics and Data Science but don't know where to start?
This course takes you from the fundamentals of Python to practical data analysis using some of the most widely used Python libraries and techniques. Instead of focusing only on Python programming concepts, you will learn how Python is actually used to work with real-world data, clean datasets, perform analysis, create visualizations, and extract meaningful insights.
Build Practical Data Analytics Skills Using Python, Pandas, NumPy, Visualization, And Exploratory Data Analysis
In this course, you will
• Build a strong foundation in Python programming for data-related tasks
• Work with NumPy arrays and perform numerical operations
• Use Pandas to import, clean, transform, filter, and analyze datasets
• Handle missing values, duplicates, incorrect data types, and other common data-quality issues
• Perform Exploratory Data Analysis (EDA) to understand datasets and identify patterns
• Create meaningful data visualizations using Python
• Analyze real-world datasets and answer business and analytical questions
• Apply Python techniques commonly used in Data Analytics and Data Science projects
• Develop practical skills that you can use in projects, interviews, and your professional career
What Is This Course About?
Python has become one of the most widely used programming languages for working with data. It is used across Data Analytics, Data Science, Machine Learning, Business Intelligence, Automation, and many other areas of the technology industry.
However, learning Python syntax alone is not enough for a career in data.
You need to know how to take a dataset, understand its structure, clean the data, transform it, analyze it, visualize important patterns, and finally communicate useful insights.
That is the approach followed in this course.
You will gradually move from Python fundamentals into practical data analytics workflows using libraries such as NumPy and Pandas. You will also work with data visualization and Exploratory Data Analysis so that you can understand how Python is applied to real-world datasets.
Learn Python With a Data Analytics Focus
If you are coming from Excel, Power BI, SQL, or another data-related background, this course can help you add Python to your existing skill set.
You will learn how to work with data programmatically instead of performing every operation manually.
You will practice important tasks such as
• Loading datasets
• Exploring data
• Selecting and filtering records
• Sorting and aggregating data
• Creating calculated columns
• Handling missing values
• Removing duplicates
• Transforming datasets
• Working with different data types
• Grouping and summarizing data
• Performing exploratory analysis
• Creating visualizations
• Finding patterns and trends in data
• Answering analytical questions using Python
Practical Learning Approach
The course is designed with a practical, hands-on approach.
Instead of learning Python concepts in isolation, you will continuously connect programming concepts with data-related use cases. You will work with datasets and apply the techniques you learn throughout the course.
This helps you understand not onlyhow to write Python code, but alsowhen and why to use a particular technique while analyzing data.
Who Is This Course For?
This course is suitable for
• Beginners who want to learn Python for Data Analytics
• Aspiring Data Analysts and Data Scientists
• Excel, SQL, or Power BI professionals who want to add Python to their skill set
• Students preparing for Data Analytics or Data Science careers
• Working professionals looking to transition into data-related roles
• Anyone who wants to learn practical Python data analysis skills
You don't need to be an advanced programmer to get started. The course builds the required Python foundation before moving into data analytics concepts.
What Will You Gain From This Course?
By the end of the course, you will have a practical understanding of how Python can be used throughout a typical data analysis workflow.
You will be able to work with datasets using Python, perform data cleaning and transformation, conduct exploratory analysis, create visualizations, and generate useful insights from data.
More importantly, you will have a foundation that you can continue building toward advanced Data Analytics, Data Science, and Machine Learning topics.
If you want to move beyond basic Python programming and learn how Python can be applied to real-world data problems, this course will give you a practical starting point.
Enroll in the course and start building your Python Data Analytics skills step by step.

Who this course is for

⭐ All the Data Professionals

Homepage

https://www.udemy.com/course/python-for-data-analytics-science

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