HARTMANN software group

Using Data Science Tools in Python Training in Las Cruces

Enroll in or hire us to teach our Using Data Science Tools in Python class in Las Cruces, New Mexico by calling us @303.377.6176. Like all HSG classes, Using Data Science Tools in Python may be offered either onsite or via instructor led virtual training. Consider looking at our public training schedule to see if it is scheduled: Public Training Classes
Provided there are enough attendees, Using Data Science Tools in Python may be taught at one of our local training facilities.
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Course Description

  
More and more organizations are turning to data science to help guide business decisions. Regardless of industry, the ability to extract knowledge from data is crucial for a modern business to stay competitive. One of the tools at the forefront of data science is the Python® programming language. Python's robust libraries have given data scientists the ability to load, analyze, shape, clean, and visualize data in easy to use, yet powerful, ways. This course will teach you the skills you need to successfully use these key libraries to extract useful insights from data, and as a result, provide great value to the business.
 
In this course, you will use various Python tools to load, analyze, manipulate, and visualize business data.
 
You will:
 
Set up a Python data science environment.
Manage and analyze data with NumPy arrays.
Manipulate and modify data with NumPy arrays.
Manage and analyze data with pandas DataFrames.
Manipulate, modify, and visualize data with pandas DataFrames.
Visualize data with Matplotlib and Seaborn.
Course Length: 2 Days
Course Tuition: $990 (US)

Prerequisites
To ensure your success in this course, you should have at least a high-level understanding of fundamental data science concepts, including but not limited to: data engineering, data analysis, data storage, data visualization, and statistics. You can obtain this level of knowledge by taking our CertNexus DSBIZ. You should also be proficient in programming with Python.

Course Outline

  

Lesson 1: Setting Up a Python Data Science Environment

Topic A: Select Python Data Science Tools

Topic B: Install Python Using Anaconda

Topic C: Set Up an Environment Using Jupyter Notebook

 

Lesson 2: Managing and Analyzing Data with NumPy

Topic A: Create NumPy Arrays

Topic B: Load and Save NumPy Data

Topic C: Analyze Data in NumPy Arrays

 

Lesson 3: Transforming Data with NumPy

Topic A: Manipulate Data in NumPy Arrays

Topic B: Modify Data in NumPy Arrays

 

Lesson 4: Managing and Analyzing Data with pandas

Topic A: Create Series and DataFrames

Topic B: Load and Save pandas Data

Topic C: Analyze Data in DataFrames

Topic D: Slice and Filter Data in DataFrames

 

Lesson 5: Transforming and Visualizing Data with pandas

Topic A: Manipulate Data in DataFrames

Topic B: Modify Data in DataFrames

Topic C: Plot DataFrame Data

 

Lesson 6: Visualizing Data with Matplotlib and Seaborn

Topic A: Create and Save Simple Line Plots

Topic B: Create Subplots

Topic C: Create Common Types of Plots

Topic D: Format Plots

Topic E: Streamline Plotting with Seaborn

 

Appendix A: Scraping Web Data Using Beautiful Soup

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Python Programming Uses & Stats

Python Programming is Used For:
Web Development Video Games Desktop GUI's Software Development
Difficulty
Popularity
Year Created
1991
Pros
Easy to Learn:
The learning curve is very mild and the language is versatile and fast to develop.
 
Massive Libraries:
You can find a library for basically anything: from web development, through game development, to machine learning.
 
Do More with Less Code:
You can build prototypes and test out  ideas much quicker in Python than in other language
Cons

Speed Limitations:

It is an interpretive language and therefore much slower than compiled languages.

Problems with Threading:

Multi-threaded CPU-bound programs may be slower than single-threaded ones do to the Global Interpreter Lock (GIL) that allows only one thread to execute at a time.

Weak on Mobile:

Although, there are a number or libraries that provide a way to develop for both Android and iOS using Python currently Android and iOS don’t support Python as an official programming language.
Python Programming Job Market
Average Salary
$107,000
Job Count
26,856
Top Job Locations

New York City

Mountain View

San Francisco
Complimentary Skills to have along with Python Programming
The potential for career growth, whether you are new to the industry or plan to expand your current skills, depends upon your interests:
  - For knowledge in building in PC or windows, phone apps or you are looking your future in Microsoft learn C#
  - For android apps and also cross platform apps then learn Java
  - If you are an Apple-holic and want to build iOS and MAC apps and then choose Objective C or Swift
  - Interested in game development? C++
  - Data mining or statistics then go with R programming or MATLAB
  - Building an operating systems? C

Interesting Reads Take a class with us and receive a book of your choosing for 50% off MSRP.