Professional Certificate of Competency in Practical Python for Engineers & Technicians

Course Overview

CPY

Python is extraordinarily good at being an all-purpose programming language. It is such a powerful language because it requires less supporting code; it speeds up the development cycle, and it makes any debugging a breeze. This professional development course is designed for engineers and technicians who need to understand the Python programming language and apply it to solve engineering problems.

At a glance

Duration
  • 3 Months
Study Mode
  • Online
Location
  • Online
Intakes
TBA
Course Type
  • Professional Certificate
  • Data Comms & Industrial IT

Course Details

Python is an object-oriented generic programming language that is particularly suited to the modern world. It is an excellent choice for introducing fundamental programming concepts as it reduces the complexity of problem-solving by hiding the intricate arcane detail ‘under the hood.’ Python can do in a single line what many programming languages require multiple lines of code to achieve.

Automation of tasks is a critical part of every engineer’s jobs today. Design probably only takes 10 percent of an engineer’s time — most of the day-to-day work is in research, testing of prototypes, debugging, production testing, and documentation. Python is now increasingly used in the automation and embedded systems world. Specific tasks for Python include testing, data collection, and automation.

Therefore, there is a growing need for Python programming skills by industry (typically manufacturing, mining, healthcare, and energy). This program focuses on giving you a solid foundation in the use of this language. This allows you to leave the program with a strong capability in programming with Python, rather than superficially skimming through the language. Naturally, you will need to apply your knowledge to engineering tasks to extend and solidify your proficiency.

This program focuses on specific engineering disciplines: electrical engineering, mechanical engineering, industrial automation, and civil engineering.

Electrical Engineering applications include file processing (conversion from one format to another such as XML to CSV), automation of test equipment and data (such as waveforms for power quality problems), and database management (such as SQL).

Mechanical Engineering is often considered to be disconnected from the need for programming knowledge. That couldn’t be further from the truth. Areas such as numerical analysis (with awkward boundary conditions) in manufacturing, automotive, energy spheres of activity, and thermodynamics (ranging from fluid dynamics to chemical kinetics) require programming knowledge. It is also imperative in computational fluid dynamics.

Civil Engineering applications include risk assessment and mitigation for floods, cyclones, earthquakes, prediction of traffic trends, stress analysis of data from bridges, analysis of vast amounts of geotechnical data.

Industrial Automation application includes analysis of vast amounts of data from processes, logging data over a Modbus communication link, and preventative maintenance. It also includes translating a PLC database and converting this into a bunch of HTML files.

The course is composed of 12 modules, covering topics such as writing effective and clean code, writing automation scripts to solve complex problems quickly, using key tools such as Anaconda, NumPy, Pandas, and Matplotlib, manipulating data for use with spreadsheets and databases, building simple models and simulations, and creating visualizations, graphical plots and schematics to showcase your output.

MODULE 1: Python Basics

  • Brief background on Python 3
  • Setting up programming environment
  • Installation of Anaconda distribution
  • Brief tour of Jupyter Notebook Server
  • Common user mistakes and misconceptions with Jupyter Notebooks
  • Basic operations and syntax
  • Basic input and output
  • Basic arithmetic operators
  • Commenting
  • Variables
  • Nesting
  • Common Errors
  • Take home exercise-Electrical/Mechanical/Civil/Industrial Automation

MODULE 2: Datatypes

  • Integers
  • Strings
  • Lists
  • Tuples
  • Dictionaries
  • Take home exercise-Electrical/Mechanical/Civil/Industrial Automation

MODULE 3: Numpy

  • Numpy Arrays
  • Numpy Array Mathematics
  • Numpy Array Manipulation
  • Take home exercise-Electrical/Mechanical/Civil/Industrial Automation

MODULE 4: Conditionals & Errors

  • Object “Truthiness”
  • Booleans
  • Conditional operators
  • if, elif and else
  • Syntax errors
  • Logic errors
  • Run-time errors
  • Common Exceptions
  • Exception Handling
  • Take home exercise-Electrical/Mechanical/Civil/Industrial Automation

MODULE 5: Looping

  • Definite vs. Indefinite loops
  • while loop – Indefinite loop
  • for loop – Definite loop
  • enumerate function
  • zip function
  • Take home exercise-Electrical/Mechanical/Civil/Industrial Automation

MODULE 6: Pandas

  • File modes
  • Reading Files
  • Writing Files
  • Saving and loading
  • Pandas Series
  • Pandas Dataframe
  • Data Loading
  • Summarizing Data
  • Handling Missing Data
  • Take home exercise-Electrical/Mechanical/Civil/Industrial Automation

MODULE 7: Data Analysis with Pandas

  • Reshaping Data
  • Data Subsetting
  • Grouping Data
  • Combining Data
  • Applied Python Engineering Project (one to two-week duration for implementation)

MODULE 8: Visualization of Dataframe with Matplotlib

  • Line chart
  • Scatter plot chart
  • Pie chart
  • Bar Chart
  • Histogram Chart
  • Take home exercise-Electrical/Mechanical/Civil/Industrial Automation

MODULE 9: Functions

  • Defining functions
  • Calling functions
  • Functions without returns
  • Argument passing
  • Take home exercise-Electrical/Mechanical/Civil/Industrial Automation

MODULE 10: Modules

  • Creating modules
  • Importing modules
  • Packages
  • Take home exercise-Electrical/Mechanical/Civil/Industrial Automation

MODULE 11 & 12: Object-Oriented Programming

  • Creating classes
  • Creating instance objects
  • Inheritance
  • Function overloading
  • Take home exercise-Electrical/Mechanical/Civil/Industrial Automation

To obtain a certificate of completion for EIT’s Professional Certificate of Competency, students must achieve a 65% attendance rate at the live, online weekly webinars.  Detailed summaries/notes can be submitted in lieu of attendance.  In addition, students must obtain a mark of 60% in the set assignments which could take the form of written assignments and practical assignments. Students must also obtain a mark of 100% in quizzes.  If a student does not achieve the required score, they will be given an opportunity to resubmit the assignment to obtain the required score.

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You are expected to spend approximately 5-8 hours per week learning the course content. This includes attending weekly webinars that run for about 90 minutes to facilitate class discussion and allow you to ask questions. This professional development program is delivered online and has been designed to fit around full-time work. It will take three months to complete.

Hear from our students

  I liked most the flexibility of online delivery mode and the after-session exercises.  

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