Course description
Python Primer for Data Science & Machine Learning
Python for Data Science Primer is a two-day course that introduces data analysts and business analysts (as well as anyone interested in Data Science) to the Python programming language, as it’s often used in Data Science in web notebooks. This goal of this course is to provide students with a baseline understanding of core concepts that can serve as a platform of knowledge to follow up with more in-depth training and real-world practice.
The course begins with quick overview of Python, with demonstrations of both script-based and web notebook-based Python, and then dives into the essentials of Python necessary to a data scientist. The tail end of the course explores a quick integration of these skills with key Data Science libraries including NumPy, Pandas and Matplotlib. This class is hands-on and includes light programming labs that introduce students to basic Python syntax and concepts applicable to using Python to work with data.
NOTE: Students heading into real project work right after training might consider a more robust hands-on course with deeper topics and lab coverage for similar subjects, such as the TTPS4873 Introduction Python for Data Science
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Who should attend?
This introductory-level course is intended for Business Analysts and Data Analysts (or anyone else in the data science realm) who are already comfortable working with numerical data in Excel or other spreadsheet environments. No prior programming experience is required, and a browser is the only tool necessary for the course.
Take Before: Students should have skills at least equivalent to the following course(s) or should have attended as a pre-requisite:
· Understanding Data Science | A Technical Overview – 1 day (helpful but not required)
· Working with Excel
Take Instead:
· Students who want a quicker overview session without the hands-on might consider the TTPS4871 Python Primer for Data Science Overview one day lecture / demo only course as an alternative.
· Students faced with real project work who want a more robust introduction to these topics should consider the three-day TTPS4873 JumpStart to Python Programming for Data Science with extended topics labs.
Follow On Courses: Our core Python, data science and machine learning training courses provide students with a solid foundation for continued learning based on role, goals, or their areas of specialty. Our learning paths offer a wide variety of related follow-on courses such as:
· TTML6802 Machine Learning Essentials with Python (3 days)
· TTPS4876 Next Level Python in Data Science (Intermediate) (5 days)
· Please see the attached Python Training Suite or Machine Learning Series list for additional topics and titles.
Training content
Please note that this list of topics is based on our standard course offering, evolved from typical industry uses and trends. We’ll work with you to tune this course and level of coverage to target the skills you need most. Topics, agenda and labs are subject to change, and may adjust during live delivery based on audience interest and skill-level.
1. An Overview of Python
· Why Python?
· Python in the Shell
· Python in Web Notebooks (iPython, Jupyter, Zeppelin)
· Demo: Python, Notebooks, and Data Science
2. Getting Started
· Using variables
· Builtin functions
· Strings
· Numbers
· Converting among types
· Writing to the screen
· Command line parameters
3. Flow Control
· About flow control
· White space
· Conditional expressions
· Relational and Boolean operators
· While loops
· Alternate loop exits
4. Sequences, Arrays, Dictionaries and Sets
· About sequences
· Lists and list methods
· Tuples
· Indexing and slicing
· Iterating through a sequence
· Sequence functions, keywords, and operators
· List comprehensions
· Generator Expressions
· Nested sequences
· Working with Dictionaries
· Working with Sets
5. Working with files
· File overview
· Opening a text file
· Reading a text file
· Writing to a text file
· Reading and writing raw (binary) data
6. Functions
· Defining functions
· Parameters
· Global and local scope
· Nested functions
· Returning values
7. Essential Demos
· Sorting
· Exceptions
· Importing Modules
· Classes
· Regular Expressions
8. The standard library
· Math functions
· The string module
9. Dates and times
· Working with dates and times
· Translating timestamps
· Parsing dates from text
· Formatting dates
· Calendar data
10. Python and Data Science
· Data Science Essentials
· Pandas Overview
· NumPy Overview
· SciKit Overview
· MatPlotLib Overview
· Working with Python in Data Science
Costs
- Price: $1,695.00
- Discounted Price: $1,101.75
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Reviews
Average rating 5
Excellent training. Even though it was online, I did not have any issues understanding or getting the answers for the questions I had. The lab exercises are interesting to apply...
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Trivera Technologies
Trivera Technologies is a IT education services & courseware firm that offers a range of wide professional technical education services including: end to end IT training development and delivery, skills-based mentoring programs,new hire training and re-skilling services, courseware licensing and...
First time in my life I have attended remote class and I find it great. Personally I don't feel there is any area which require improvement!