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Data is everywhere—in sales figures, market research, transportation cost, logistics, and more. Let’s face it: business aggregates data rapidly. Collecting data is one thing, but using it for planning and decision-making is a completely different story. Forget about Excel pivot tables and charts. If you want to make good decisions based on data you own, you need to know how to derive insights from that data. That’s why we’re introducing a new course on the Python programming for data analysis.

Python is a powerful general-purpose programming language that is becoming world’s most popular language for data analysis. It’s a very simple and elegant language that promotes good coding habits. That’s why it’s especially recommended for beginners. Python is very popular among data scientists because it combines data science libraries and algorithms with the expressive power of a regular programming language.

Python for data science

Python is the hottest analytical skill on the job market—it not only solves real data problems but also creates business-ready reports and stunning graphics, all with cutting-edge algorithms that you don’t even need to understand to use.

This interactive Intro to Python course covers all the basics of Python you need to know to mine through data and perform data analysis. You’ll start your Python programming journey by learning how to import data into Python, use data frames, and, most importantly, think analytically.

You don’t need any programming or data science background to learn Python with us! Open yourself to more data science and big-data job opportunities, and take your career to the next level. No additional software or talking-head tutorials—just you, your browser, and 141 interactive exercises. Start learning now!

What Are the Requirements?

Just a web browser

This Course Will Teach You How To:

  • Import CSV files into Python
  • Create simple data visualizations with Python’s visualization library, matplotlib
  • Use Python’s data analysis library, pandas
  • Perform simple analyses on data using Python
  • Use Python to do basic calculations
  • Work with missing values
  • Create variables in Python
  • Use and create data frames in Python
  • Filter data frames in Python
  • Add new columns to existing data frames

Who Should Take This Course?

  • Anyone who needs to present data to a group or publish a data presentation
  • Anyone who wants to create meaningful and compelling charts
  • Anyone interested in data science or programming
  • Data and business analysts
  • Beginner data scientists
  • Students taking classes in data analysis
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    One to Rule 'Em All

    Includes 36 courses Python Basics. Part 1, Python Basics. Part 2, Python Basics. Part 3, Python Data Structures in Practice, Built-in Algorithms in Python, Working with Strings in Python, SQL Basics, SQL Practice Set, SQL JOINs, Standard SQL Functions, Creating Basic SQL Reports, Window Functions, Revenue Trend Analysis in SQL, How to INSERT, UPDATE, and DELETE Data in SQL, Recursive Queries, Creating Tables in SQL, Statistics 101, SQL Basics in MS SQL Server, How to Insert, Update, or Delete Data in MS SQL Server, Common Functions in MS SQL Server, Revenue Trend Analysis in SQL Server, Creating Basic SQL Reports in SQL Server, Window Functions in MS SQL Server, Recursive Queries in MS SQL Server, GROUP BY Extensions in MS SQL Server, Introduction to Python for Data Science, How to Read and Write CSV Files in Python, How to Read and Write JSON Files in Python, SQL Basics in PostgreSQL, PostgreSQL JOINs, SQL Practice Set in PostgreSQL, Window Functions in PostgreSQL, Recursive Queries in PostgreSQL, Writing User-Defined Functions in PostgreSQL, PostGIS, How to Read and Write Excel Files in Python

    Bundle price $99

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    75%
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    $187

    Basic Data Analytics

    Includes 5 courses SQL Basics, SQL Practice Set, SQL JOINs, Statistics 101, Introduction to Python for Data Science

    Bundle price $45

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    Table of contents

    Progress: 0% completed 0 of 141 exercises done

    1. Python Basics

    Discover how to write simple programs using Python, the most popular language for data analysis and data science.

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    2. Data Frames in Pandas

    Learn how to work with tabular data in Python. In this part, you'll know DataFrame, the basic data structure of the popular data analysis library pandas.

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    3. Data analysis and grouping

    Compute basic statistics and group rows of DataFrames.

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    4. Data preprocessing

    Learn how to deal with errors in your datasets.

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    5. Data visualization with matplotlib

    Understand the basics of matplotlib to quickly create visualization.

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    6. Challenge

    Consolidate and check your knowledge of Python and pandas.

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