Now is the time to get certified for Python!

ITS-303 Python (Information Technology Specialist)

Formerly Microsoft MTA 98-381

There are six Practice Tests with preparation questions from all knowledge areas

to prepare for the ITS-303 Python (Information Technology Specialist) exam at Certiport (Pearson VUE).

Every question has an explanation and a Try-It-Yourself-Code

which you can run to better understand the topic.

You can download the Try-It-Yourself-Code for all questions.

(The download link will be in your welcome message.)

Exam Syllabus

Operations using Data Types and Operators

• Evaluate expressions to identify the data type Python assigns to variables:
  str, int, float, and bool

• Perform and analyse data and data type operations:
  Data type conversion, indexing, slicing, construct data structures, lists, list operations

• Determine the sequence of execution based on operator precedence:
  Assignment, comparison, logical, arithmetic, identity (is), containment (in)

• Select operators to achieve the intended result:
  Assignment, comparison, logical, arithmetic, identity (is), containment (in)

  
  

Flow Control with Decisions and Loops

• Construct and analyze code segments that use branching statements:
  if, elif, else, nested and compound conditional expressions

• Construct and analyze code segments that perform iteration:
  while, for, break, continue, pass, nested loops, loops that include compound conditional expressions

Input and Output Operations

• Construct and analyze code segments that perform file input and output operations:
  open, close, read, write, append, check existence, delete, with statement

• Construct and analyze code segments that perform console input and output operations:
  Read input from console, print formatted text (string.format() method, f-String method), use command-line arguments

Code Documentation and Structure

• Document code segments:
  Use indentation, white space, comments, and documentation strings; generate documentation by using pydoc

• Construct and analyze code segments that include function definitions:
  Call signatures, default values, return, def, pass

Troubleshooting and Error Handling

• Analyze, detect, and fix code segments that have errors:
  Syntax errors, logic errors, runtime errors

• Analyze and construct code segments that handle exceptions:
  try, except, else, finally, raise

• Perform unit testing
  Unittest, functions, methods, and assert methods (assertIsInstance, assertEqual, assertTrue, assertIs, assertIn)

Operations using Modules and Tools

• Perform basic file system and command-line operations by using built-in modules:
  io, os, os.path, sys (importing modules, opening, reading and writing files, command-line arguments)

• Solve complex computing problems by using built-in modules:
  Math (fabs, ceil, floor, trunc, fmod, frexp, nan, isnan, sqrt, isqrt, pow, pi) datetime (now, strftime, weekday), random (randrange, randint, random, shuffle, choice, sample)

Why learn Python?

Python is easy to learn. The syntax is simple and the code is very readable. With Python, you can write programs in fewer lines of code than with most other programming languages. The popularity of Python is growing rapidly. It is now one of the most popular programming languages. Python has a wide variety of applications. It is used for automation, web application development, artificial intelligence, data science and so on:

Automation

Python can make life easier by automating many tasks, such as scraping a website to collect data, automating test cases in software development, or automating everyday office tasks. Python can easily access and read all kinds of files, which opens up the possibility of saving a lot of time by automating repetitive tasks.

Web Development

Python is a good choice for rapid web application development. With many frameworks like Django, Pyramid, and Flask, you can develop web applications with great speed using Python. Python is used on the server side of web development. You can use Python to interact with database and create RESTful API services.

Artificial Intelligence

The near future will be the era of artificial intelligence. In the past, computers and machines were used to perform mathematical calculations at very high speeds, but now many large organizations and researchers are working to develop intelligent systems that can perform tasks like a human. To some extent, machines are able to understand human emotions and their natural language. They can mimic certain human actions that were not possible before. Again, Python is very popular for developing AI systems.

Data Science

Earlier, Python was mainly used to build applications and write scripts to automate tasks, but now a brand new trend of data science has given Python an even bigger boost. Data scientists are heavily dependent on Python because it is so simple, has a large community, and can perform huge calculations with ease.

Python is being used in a wide variety of fields, and there are no signs that this trend is coming to a halt. It's safe to say that Python is here to stay for the long haul in this ever-changing and evolving IT industry.