Online Course – Certified Professional Internship in Data Analysis with Pandas and Python from Google and Packt Institute

Learning Pandas: Analyzing data in Python made easy. The course includes programming in Python and analyzing data with Pandas, including installation, basic Python concepts, handling series and DataFrames, managing text data, GroupBy methods, merging DataFrames, managing dates and times, input/output operations, data visualization, and customizing Pandas.

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קורס אונליין - התמחות מקצועית מוסמכת בניתוח נתונים עם Pandas ו-Python של Google ו-Packt Institute

Professional Certificate

Intermediate level

No prior knowledge required

Time to complete the course

7-day free trial

No unnecessary risks

Skills you will acquire in the course

  • Jupyter Lab Training
  • Data analysis with Pandas
  • Using the Matplotlib library
  • Installing and configuring Anaconda
  • Python for Data Science

What you will learn in the course

Courses for which the course is suitable

  • Analyze data
  • Data Scientist
  • Data Analyst
  • Data manipulation expert
  • Advanced Data Analyst
  • Data Analysis Solutions Developer

Internship – 3-part course series

Course Description

This course starts by installing Anaconda and Jupyter Lab for Python and Pandas, and provides a basic understanding of Python before diving into Pandas for data analysis. You will learn Series and DataFrame data structures for effective data management and manipulation.

Key topics include:

  • Handling dates
  • Perform file I/O operations that are essential for real-world data tasks
  • Advanced data visualization using Matplotlib
  • Advanced Pandas capabilities and settings to enhance data manipulation capabilities

Course objectives

At the end of the course, you will master data analysis techniques, be skilled in handling complex data sets, perform in-depth analysis and present insights visually, and prepare you for advanced roles in data analysis and manipulation.

The course is intended for:

  • Data analysts
  • Data Scientists in Data Science
  • Professionals who are interested in deepening their skills in data manipulation and analysis using Pandas

Methodological Learning Project

Learners will tackle real-world projects such as:

  • Filtering and extracting data from complex DataFrames
  • Merging data sets
  • Performing GroupBy operations to discover insights

They will work with text data, dates, and times, and apply advanced Pandas capabilities to solve authentic data analysis problems. Through hands-on projects, learners will visualize data using Matplotlib, present their findings effectively, and prepare themselves for professional data analysis roles.

Details of the courses that make up the specialization

Data Analysis Fundamentals with Funds and Python

Course 1 • 9 hours

Course Details

What you’ll learn
  • Explain how to get around and utilize Jupyter Lab for Python programming.
  • Write Python code, including functions and data structures.
  • Manipulate and analyze data using Funds DataFrames.
  • Apply data cleaning and sorting techniques to prepare data sets for analysis.
Skills you will acquire
  • Category: Data Analysis
  • Category: Funds DataFrames
  • Category: Anaconda definition
  • Category: Basic Python Course
  • Category: Python Programming

Intermediate data analysis techniques with PANDAS

Course 2 • 12 hours

Course Details

What you’ll learn
  • Take advantage of advanced column selection and processing techniques in Pandas.
  • Use various filtering techniques to improve the accuracy of data extraction.
  • Effectively apply Funds methods to effectively clean and prepare data.
  • Manage and manipulate data with MultiIndex and text data in pools to handle data comprehensively.
Skills you will acquire
  • Category: MultiIndex Funds
  • Category: Data Cleanup
  • Category: Funds DataFrames
  • Category: Data Filtering
  • Category: Data Extraction

Advanced data analysis and data visualization with Funds

Course 3 • 5 hours

Course Details

What you’ll learn
  • Demonstrate control over exporting and importing data in CSV and Excel formats using Funds.
  • Create and customize data diagrams using Matplotlib to effectively present insights.
  • Change Funds settings and parameters to optimize data analysis for specific needs.
  • Apply advanced Funds techniques to streamline data workflows and improve efficiency in data processing and analysis.
Skills you will acquire
  • Category: Funds Integration with Excel
  • Category: Python Matplotlib
  • Category: Advanced Funds
  • Category: The Pands Show
  • Category: Data Analysis in Python

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