**Includes exercises and a Python Project!**

If you need to get a better tool for handling data, it’s time you got to know Python, and this Python for Beginners course is the perfect place to start.

Python is one of the most popular languages for data analysis and business intelligence. In this introductory course, we assume no prior knowledge and guide you through getting set up and started.

With practice exercises and a full end of course project to complete, you’ll quickly get to grips with this powerful programming language.
 
 

Happily, there is a growing number of tools to help make sense of the volume of raw data now available. Alteryx is one of those.
In this Introduction to Alteryx course, we show you how to get started with the Alteryx Designer and set you on a path to becoming an Alteryx developer.
You don’t need any previous knowledge of Alteryx to take this course. These Alteryx tutorials will show you everything you need to know to get started. However, an intermediate to advanced Excel understanding is useful.

We’ll start by introducing you to R, why it’s used by data scientists, and what it’s capable of. After that, we get you set up in R Studio and show you how to prepare the R Workspace. We then launch into Data Types in R, Coding Style in R.
We also show you how to import data into R Studio from various file formats before launching into the essential R components – Vectors, Matrices, Arrays, Lists, Factors, Loops, Functions, Dataframes and so much more.
We end the course with a mini-project where we pull everything you have learned together and set you an R Programming challenge.

In this practical, hands-on course you’ll learn how to program in R and how to use R for effective data analysis, visualization and how to make use of that data in a practical manner. You will learn how to install and configure software necessary for a statistical programming environment and describe generic programming language concepts as they are implemented in a high-level statistical language.
The course covers practical issues in statistical computing which include programming in R, reading data into R, accessing R packages, writing R functions, debugging, profiling R code, and organizing and commenting on R code. Blending practical work with solid theoretical training, we take you from the basics of R Programming to mastery.
R coding experience is either required or recommended in job postings for data scientists, machine learning engineers, big data engineers, IT specialists, database developers and much more. Adding R coding language skills to your resume will help you in any one of these data specializations requiring mastery of statistical techniques.
Together we’re going to give you the foundational education that you need to know not just on how to write code in R, analyze and visualize data but also how to get paid for your newly developed programming skills.
 
 

In this practical, hands-on course you’ll learn how to program using Python for Data Science and Machine Learning. This includes data analysis, visualization, and how to make use of that data in a practical manner.
We'll go over some of the best and most important Python libraries for data science such as NumPy, Pandas, and Matplotlib +

• Pandas — A Python library created specifically to facilitate working with data, this is the bread and butter of a lot of Python data science work.

This Machine Learning with Python course dives into the basics of machine learning using Python. You'll learn about supervised vs. unsupervised learning, look into how statistical modeling relates to machine learning, and do a comparison of each.
Python coding experience is either required or recommended in job postings for data scientists, machine learning engineers, big data engineers, IT specialists, database developers, and much more. Adding Python coding language skills to your resume will help you in any one of these data specializations requiring mastery of statistical techniques.
Become a professional Data Scientist and learn how to use NumPy, Pandas, Machine Learning and morea professional Data Scientist and learn how to use NumPy, Pandas, Machine Learning and more.
Learn Python for Data Science & Machine Learning from A-Z
Our main objective is to give you the education not just to understand the ins and outs of the Python programming language for Data Science and Machine Learning, but also to learn exactly how to become a professional Data Scientist with Python and land your first job.

• NumPy —  A library that makes a variety of mathematical and statistical operations easier; it is also the basis for many features of the pandas library.

We understand that theory is important to build a solid foundation, we understand that theory alone isn’t going to get the job done so that’s why this course is packed with practical hands-on examples that you can follow step by step. Even if you already have some coding experience, or want to learn about the advanced features of the Python programming language, this course is for you!
Together we’re going to give you the foundational education that you need to know not just on how to write code in Python, analyze and visualize data and utilize machine learning algorithms but also how to get paid for your newly developed programming skills.
In this practical, hands-on course you’ll learn how to program using Python for Data Science and Machine Learning. This includes data analysis, visualization, and how to make use of that data in a practical manner.
We'll go over some of the best and most important Python libraries for data science such as NumPy, Pandas, and Matplotlib +
This Machine Learning with Python course dives into the basics of machine learning using Python. You'll learn about supervised vs. unsupervised learning, look into how statistical modeling relates to machine learning, and do a comparison of each.
Python coding experience is either required or recommended in job postings for data scientists, machine learning engineers, big data engineers, IT specialists, database developers, and much more. Adding Python coding language skills to your resume will help you in any one of these data specializations requiring mastery of statistical techniques.
NumPy and Pandas are great for exploring and playing with data. Matplotlib is a data visualization library that makes graphs as you’d find in Excel or Google Sheets. Blending practical work with solid theoretical training, we take you from the basics of Python Programming for Data Science to mastery.

• • Pandas — A Python library created specifically to facilitate working with data, this is the bread and butter of a lot of Python data science work.

Together we’re going to give you the foundational education that you need to know not just on how to write code in Python, analyze and visualize data and utilize machine learning algorithms but also how to get paid for your newly developed programming skills.
 
 
 

LabVIEW is graphically based, meaning you drag around various building blocks and connect them in a data flow architecture. It’s like drawing a block diagram, except you’re drawing your code, as opposed to text-based languages like C# & VHDL where you type out in text what you want the software to do.

There are some additional corner cases out there, but this covers most applications we see at Viewpoint. Historically, LabVIEW has been widely adopted in the automated test realm, becoming the de facto standard in that application space, whereas more recently it’s been gaining traction within the realm of industrial embedded monitoring and control.

LabVIEW is a software development environment created by National Instruments. Originally it was focused on taking measurements from various lab instruments, but it’s expanded drastically from its inception. LabVIEW is not a coding language, it’s a development environment. The language is called “G”, but most people refer to LabVIEW as if it’s a language (i.e., most people would say “it’s coded in LabVIEW”).

Where you’re going to learn how to become a professional Python Developer and create programs, apps, scripts, games and so much more...

Blending practical work with solid theoretical training, we take you from the basics of Python Programming to mastery, giving you the training you need not just to create software programs, scrape websites, and build automations, but also the foundational understanding of data science and visualization so you can become a well-rounded Python Programmer.

Even if you already have some coding experience, or want to learn about the advanced features of Python, this course is for you! In this course, you’ll learn Python 3.

Together we’re going to give you the foundational education that you need to know not just on how to write code in Python, create various scripts and softwares but also how to get paid for your newly developed programming skills.