הקורסים החמים ביותר והנדרשים ביותר עכשיו באונליין-לייב עם הנחות חסרות תקדים

חייגו עכשיו: 073-2865544

Python course for Data Analysis (קורס פייתון)

Description:

Python is a general purpose language, and is very user-friendly for new users. In terms of structure and syntax, it’s a well-designed, intuitive, and exceedingly powerful general-purpose programming language. As such it has many features that definitely won’t be relevant for everyone. In last year’s we have seen that Python is an increasingly popular tool for data analysis. And it is not necessary to become proficient in Python programming to be able to perform data analysis. Still, you need to invest time to learn the fundamentals of the language before you jump into applications.

לחצו כאן Software Developers לקורס פייתון עבור

לחצו כאן Spark with Python לקורס

This Python course is designed to build strong basis in Python and its related packages for operating with data. The course includes the main tools for data analysts and other users with little or no serious programming experience who just want to get things done in data analysis.

The Python course includes the basic and intermediate Python programming and the most important libraries for data analysis:

Numpy is the fundamental package for scientific computing with Python. A good understanding of Numpy will help you use tools like Pandas effectively.

Matplotlib is a widely-used package for scientific graphics. This part will include an introduction to the matplotlib objects, to their basic functionalities and a survey of the basic plot types.

Pandas is a package for data manipulation, and gives a set of easy-to-use capabilities resembling SQL (on the data processing side) and Excel (on the visualization side).

Course Objectives:
  • To get an intermediate skill level of Python programming to perform data analysis.
  • To use the numpy library to create and manipulate arrays.
  • To create data visualizations using matplotlib with python.
  • To use the pandas with Python to create and structure data.
  • To work with various data formats within python, including: JSON, HTML, and MS Excel Worksheets.

This course is intended for data analysts, BI experts, developers and everyone who wants to perform a data manipulation with Python.

  • Practice at home at least 1 hour for each hour at class
  • Familiarity with some command-line and shell tool: powershell / bash / cmd
  • Familiarity with basic SQL: SELECT, WHERE, GROUPBY, JOIN
  • Familiarity with programming in any language: Java / C# / C++ / Python / PL/SQL, etc

Basic Python

  • Fundamentals
    • Intro
    • Python essentials
    • The working environment
  • Data types
    • Numbers
    • Strings
    • Booleans
    • None
  • Collections
    • Lists
    • Tuples
    • Dictionaries
    • Sets
  • Control flow
    • if…else
    • for…in
    • list comprehension
    • while
    • continue & break
  • Textual interface
    • input
    • format

Intermediate Python

  • Functions
    • User-defined functions
    • *args and **kwargs
    • Built-in functions
    • Lambda expressions
  • Debugging and Error Handling
  • Text files
  • The standard library
    • import
    • datetime

Python Tools for working with Data

  • The NumPy library
    • Array
    • Broadcasting
  • The matplotlib library
    • matplotlib objects
    • Plotting
    • Seaborn
  • The pandas library
    • Series and Index
    • DataFrame
    • GroupBy
    • Visualizations
  • Practice: Use cases and EDA
    • Diamonds
    • IMDB
    • San Francisco Crime
    • Adult US Census
  • General tools
    • Intro to regular expressions (re)
    • API’s and Connecting with Data Resources
      • JSON
      • Intro to working with DBs with SQLAlchemy package
      • Intro to HTTP Web requests with requests package
מורן אלקובי מרצהעמית הינו Data Scientist בחברת נאיה טכנולוגיות, מנהל תחום Data Science בנאיה אקדמי ומרצה בכיר ומוביל בתחום. עמית בוגר הטכניון בתואר הנדסת חשמל ופיזיקה ובעל ניסיון רב בהובלת פרויקטים טכנולוגית עתירי מידע
  • טרם נקבע מועד פתיחה
  • 09:00-16:30 daysימים ושעות
  • 48academic hours שעות אקדמיות
  • בסיסיcourse levelרמת הקורס
  • עבריתlanguageשפת הדרכה
  • לבדיקת התאמה לקורס
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