EECE 1317 (ENGINEERING PROGRAMMING)

Learning Outcomes

By the end of this course, students should be able to:

  • Assess Python computer programmes, applied to solve engineering problems, and recommend corrections to erroneous code
  • Create a complete and sound computer programmes using Python language to solve wide-range of scientific and engineering problems.

Lecture 1 – Introduction to Computers and Programming

In this lecture you will learn about :

  • The basic hardware and software parts of a computer.
  • How Computers Store Data
  • How a Program Works
  • Using Python
  • Designing a program

NOTES

Lecture 2 – Input and Output Processing

In this lecture, you will learn about:

  • How to display statements using the ‘print’ function
  • Numbers and Operations

NOTES

Lecture 3 – Numbers and Sequence

In this lecture, you will know more about:

  • Numbers and Operation
    • Formatting
  • Types of Numbers
    • Integer (int)
    • Float (float)
    • Complex (complex)
  • Sequence Types

NOTES

Lecture 4 – Sequence and ‘if’ statements

In this lecture, you will learn about:

  • List, Tuples and Useful Built-in Functions
  • Indexing and Slicing a sequence
  • ‘if’ statements
    • Conditional Tests
    • ‘if’ and ‘if-else’ statements

NOTES

Lecture 5 – ‘if’ statements and Dictionaries

In this lecture, you will learn about:

  • ‘if-elif-else’ statements
  • Dictionaries

NOTES

Lecture 6 – ‘while’ loop

In this lecture, you will learn about:

  • while loop vs for loop
    • Examples and Activities
  • Using ‘break’
  • Usingcontinue

NOTES

Lecture 7 – Functions

In this lecture, you will learn about:

  • ‘Functions’ in python
    • Introduction
    • Defining a Function
    • Passing Arguments
    • Return Values
    • Passing a List

NOTES

Lecture 8 – Random Numbers

In this lecture, you will learn about:

  • Generating Random Numbers
  • Storing Your Functions in ‘Modules’
    • About ‘Modules’
    • Creating and Importing ‘Modules’
    • Importing Specific Functions in ‘Modules’
  • Files
    • open()
    • read()
    • close()
    • readlines()
    • w, r, a modes
  • Exceptions

NOTES

Lecture 9 – Functional Tools

In this lecture, you will learn about:

  • Functional Tools
    • lambda
    • map
    • filter
    • list comprehension
    • reduce

NOTES

Lecture 10 – SymPy

In this lecture, you will learn about:

  • ‘Symbol’ vs ‘symbols’
    • substitute a variable with a value using ‘subs’
    • expand
  • Numeric Types
    • Rational and RealNumber
    • float() and evalf()
  • Differentiation
  • Integration
  • Matrix
  • Other SymPy Functions

NOTES

Lecture 11 – NumPy

In this lecture, you will learn about:

  • Arrays – a new data type
    • Vectors (1d-arrays)
      • numpy.arange
    • Matrices (2d-matrix)
    • Convert from array to list or tuple

NOTES

Lecture 12 – Data Visualization and Pandas

In this lecture, you will learn about:

  • Data Type
    • Series
    • Data Frame
  • Create Panda Series
    • From dictionary
    • From list
  • Plotting Data in Panda Series
  • Using pyplot

NOTES