Data Analytics with R Training in Munich, Germany
Enroll in or hire us to teach our Data Analytics with R class in Munich, Germany by calling us @303.377.6176. Like all HSG
classes, Data Analytics with R 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, Data Analytics with R may be taught at one of our local training facilities.
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We offer private customized training for groups of 3 or more attendees.
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Course Description |
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| This course provides an overview of the basic to advanced features of
the R programming language. It is presented as a combination of lectures
and hands-on exercises. Course Topics: ... Data Science Basics ... R
Language Basics ... Intermediate R ... Charting and Graphing ...
Statistical Processing ... Introduction to Text Analytics and the tm
Package ... Introduction to Collaborative Filtering ... Implementing a
Recommendation Engine
Course Length: 3 Days
Course Tuition: $1190 (US) |
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Prerequisites |
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| Prior to attending this course, students should be familiar with statistical analysis concepts. Prior programming or scripting experience is strongly recommended but not required. | |
Course Outline |
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Upon completion of this course attendees will be able to:
• Describe the data science basics
• Write R programs that perform data analysis
• Use scalars, vectors, and functions in the programs
• Use matrices, factors, and data frames
• Generate R graphs and charts
• Perform statistical processing
• Implement a recommendation engine using collaborative filtering
I. Data Science Basics
II. R Language Basics
A. Scalars
B. Vectors
C. Functions
III. Intermediate R
A. Matrices
B. Factors
C. Data Frames
IV. Charting and Graphing
V. Statistical Processing
A. Linear Regression
B. Logistic Regression
VI. Text Analytics
A. Introduction to Text Analytics
B. Introduction to the ‘tm’ Package
VII. Collaborative Filtering
A. Introduction
B. Implementing a Recommendation Engine
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Python Programming Uses & Stats
Python Programming is Used For:
Web Development
Video Games
Desktop GUI's
Software Development
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Difficulty
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Popularity
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Year Created 1991 |
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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
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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
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Job Count
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Top Job Locations
New York City Mountain View San Francisco |
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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
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Interesting Reads Take a class with us and receive a book of your choosing for 50% off MSRP.
