Testers Most Demanding Skills-2026 |AWS-BDD-Python-Test Case

Learn how to format and fill test case columns, create unique test case IDs (such as DC001 or DC_001), and embed module information in the id for clear traceability.

Craft a precise test case description that clearly defines what will be tested, such as admin login with valid credentials or money withdrawal, using minimal words and clear expectations.

Define test case IDs and descriptions as mandatory, and document prerequisites like clearing browser cookies or required logins.

Learn to write clear, serial test case steps using exact element names and reproduce-ready instructions, including navigating to pages, adding items to cart, and checking out.

Define and manage test data to shape expected outcomes across test cases. Use data sheets or Excel sheets, handle sensitive data safely, and avoid junk data.

Define the expected result for each test case by deriving it from site requirements, detailing per-step outcomes, including login scenarios and messages like welcome, to ensure clear pass/fail criteria.

Learn to write formatted test cases with clear expected versus actual results, and define status using pass, fail, ignored, and blocked during test execution.

Explore how to use the comments column in formatted test cases to document execution results, defects, blockers, and rationale, including binding details and why tests fail.

Add an optional priority column to test cases, marking high, medium, and low priorities, so under tight deadlines you can filter and execute the most important tests first.

Highlight the optional type column in test cases, define test categories such as functional and usability testing, and show how filtering by type guides scheduling and team assignment.

Discover how to use an optional bug id column to link test cases with defect IDs in bug management tools like JIRA, enabling clear defect tracking and efficient defect reporting.

Outline the aws and cloud services roadmap for testers, guiding you from setup to practical use cases—virtual machines, images, s3 buckets, and security features to boost interviews and resumes.

Explore how AWS cloud services enable testers to rapidly set up diverse testing environments, run parallel nodes, replicate client setups, and deploy microservices without downtime, all with secure, cost-effective access.

Set up a free aws account by verifying with a debit or credit card. Activation occurs within 24 hours, and free trial services run for 750 hours or one year.

Create your first linux virtual machine on ec2 by launching an instance with default settings, adding a tag, and configuring a security group and a key pair.

learn how to start an ec2 linux instance, connect via web or putty with a pem key converted to ppk, log in as ec2-user, and run commands.

Create and connect a Windows virtual machine on EC2, selecting a Windows image, configuring storage and security for RDP, generating a key, and accessing via remote desktop.

Clone an existing ec2 virtual machine by creating an image and launching new instances with the same software and configuration, including java, tomcat, and openjdk.

Learn test driven development (tdd) and its unit testing cycle. Write test cases for each method before coding, then implement, run tests, and refactor within the BDD framework.

Learn behavior driven development (bdd) as a top down automation framework that defines end to end application behavior in plain language (gherkin) and automates it with step definitions.

Explore the differences between TDD and BDD, including who writes the scenarios, the shift from unit testing to end-to-end acceptance testing, and the role of gherkin for business users.

Identify the common BDD framework files—feature file in gherkin, step definitions, and a render file to trigger execution and generate reports.

Define application behavior with gherkin in a BD framework by writing end-to-end scenarios in feature files using given, when, then, and keywords like feature, scenario, background, outline, and data table.

Create and organize behavior-driven tests by writing a .feature file in notepad plus plus, using the feature keyword to define a feature and its description, and outlining scenarios.

Explore how the Gherkin scenario keyword defines multiple test cases under a feature to test end-to-end behavior, and name scenarios in simple English for registered user journeys.

Learn how to model test cases with Gherkin steps using given, when, then; define starting points, login scenarios, and step-driven test flow.

Explore gherkin basics by using when and then to write actions and verifications in a feature file. Learn how end chains multiple actions and verifies outcomes in scenarios.

Explore the Gherkin background step, learn when to use it to share a common given across all scenarios in a feature, and see how background runs before each scenario.

Define step arguments in Gherkin to pass test data as input to automation steps, linking feature files, scenarios, and step definitions for flexible testing.

Master Gherkin scenario outline for data-driven testing using examples and data tables to run a login scenario with multiple usernames and passwords.

Learn how to use comments and a triple-quoted docstring in Gherkin to pass large data as the last argument to a step, using hash comments and email workflow examples.

Explore how tags control execution in feature files, scenarios, and outlines, and selectively run smoke, sanity, and regression tests. Learn tag inheritance from feature to scenarios and examples.

Explore why software testers should learn Python to automate with Selenium, APM, and Robot Framework, and to perform data analysis with NumPy and pandas.

Learn to set up Python on a Windows 64-bit machine by downloading Python 3.7, installing it, configuring the environment variable, and verifying the installation.

Download and install PyCharm community edition to set up Python development. Create a new project, select a Python interpreter (e.g., Python 3.7), and adjust the appearance for easier coding.

Configure pip on Windows by setting the Python scripts path in system variables and verify its accessibility in the command prompt, then use it to install and download Python packages.

Set up a Python project in PyCharm, create a Python file, and write a print with comments; learn indentation and how to run code from the IDE or command prompt.

Discover how to declare and use variables in Python, define multiple variables in one line, assign the same value to several variables, and explore constants and typecasting.

Master taking user input in python, storing it in variables, and printing results while exploring variables, data types, concatenation, and multi-statement lines.

Learn how to use variables and constants in Python, including uppercase naming conventions and the fact that Python has no true constants, plus type casting between strings and integers.

Explore Python's standard datatypes—numbers, strings, lists, tuples, and dictionaries—learn how Python infers types from input, and differentiate list vs tuple and fetch via keys.

Learn Python condition handling with if, else, and elif through practical automation examples. Practice input handling, typecasting, and evaluating even numbers in real scenarios.

Master two-condition handling in python by using if and else to check even numbers, input conversion, and proper indents, with emphasis on code blocks and output messages.

Learn how to handle multiple conditions in Python using if, elif, and else, including checks for negative, zero, positive numbers and even numbers, with a default else path.

Explore nested condition handling by evaluating a user input number for negative or positive, then for even or odd, using two different approaches to implement nested if statements.

Explore how to handle conditions with logical or and logical and in Python, including input validation for marks and classifying numbers as valid or invalid, and as positive even or odd.

Explore loops in programming and automation, learning how to repeat tasks with for and while loops and conditions. See practical examples like printing hello and retrying database connections.

Master for loops with a final range in Python: the loop starts at zero by default and excludes the final value, with optional starting points and int input handling.

Learn to use Python for loops with start and end ranges to print multiplication tables, and format output by typecasting between int and string with user input.

Learn the advanced for loop to iterate over lists and tuples, including for i in list, summing values, and applying the same approach to tables, with list vs tuple differences.

Master the while loop with an initial value, a condition, and increments to run and print. Build a multiplication table from user input using typecasting and i += 1.

Explore Python string handling basics, define strings with double quotes, single quotes, or triple quotes, and perform operations like concatenation, multiplication, input and typecasting using practical examples.

Fetch substrings in Python by start and end indices, using zero-based indexing and range slicing. Understand starting, ending guidance, and how index out of range errors occur.

Explore how to manipulate strings in Python by calculating length, converting to uppercase and lowercase, and applying capitalization. Learn common string operations used in automation, length, upper, lower, and capitalized.

Discover how to remove spaces from strings using left strip, right strip, and strip in Python, to compare actual results with expected results in automation.

Explore advanced Python string operations, including replacing substrings and characters, finding indices, removing spaces, and splitting strings into lists for word-level processing.

Learn how to compare strings in python for automation, covering case sensitive and insensitive comparisons, trimming spaces with strip, and using upper or lower to normalize data.

Define a Python list with square brackets to hold multiple data types, index from zero, slice ranges, loop through items in two ways, and measure length with len.

Learn to manipulate lists by concatenating two lists, retrieving length, and performing update, insert, and delete operations by value or index, including handling first versus all occurrences.

Explore what a tuple is, how it differs from a list, store data in parentheses, fetch by index, measure length, and concatenate while preserving immutability.

Concatenate two tables with the plus operator, then observe that the table supports read operations only, while lists support read and write, including insert, update, and remove.

Learn to define and use a dictionary in Python, store data as key-value pairs with unique keys, fetch values by key, and compare with lists.

Learn how to create and manipulate Python dictionaries, including adding, updating, deleting entries, and retrieving all keys and values with dict methods.

Learn what functions are in Python, why they improve reusability and modularity, and how to define and call them to avoid code duplication.

Learn the rules to create functions using def, indentation-based bodies signaled by colons, and the return statement, including optional first-line comments and how non-returned lines behave.

Explore different types of Python functions, from no-argument to argument-taking forms, with printing and type casting for concatenation; the lesson previews returning values in a future example.

Learn to design Python functions with and without return values, using separate multiply and addition helpers and the return keyword to reuse results.

Learn Python file handling by opening files with open(), selecting modes (read, write, append), and using read, read line, and partial reads to fetch data from text files.

Read a file character by character and line by line, using a loop to print each character and another loop to read and print lines until end of file.

Learn how to write data to a .txt file in Python using the write method in write mode. Understand how appending adds new data without erasing existing content.

Explore file handling with read line operations and manage the cursor using tell and seek to display and move the cursor position.

Learn how to define a class in Python, create objects, call class functions, and understand the self parameter.

Define a class and implement three function types: no-argument no-return, argument only, and argument with return. Demonstrate using self, def, and object calls.

Explore Python constructors as a special method __init__, which initializes objects by taking self and optional arguments, automatically runs on object creation, and cannot return a value.

Learn why constructors initialize resources, ensuring a single database connection at object creation so methods read from tables E, B, and C without duplication.

Import a Python module to create a class object in another file, instantiate the class with required constructor arguments, and call its methods using the object's dot notation.

Discover how Python modules are defined as Python files with executable code, module functions, and classes, and learn about class members, properties, and constructors.

Import modules to access functions and classes, noting that module code runs on import; call functions via the module name, and instantiate classes to invoke methods, including constructors.

Generate test data in python with the faker library, install and configure faker, then produce name, email, and city records and write to an excel sheet.

Generate data with the xlwp library by creating a workbook and worksheet, writing 10,000 name, address, and email records to an output file, then append more data.

Build an interactive Python data generator that prompts for records and data type options such as full name, address, email, and phone number, using a base module and generation flow.

Generate realistic test data by parsing user-selected options, looping over records, and producing names, addresses, emails, and phone numbers, then saving the results to a file.

Explore rest api testing with Postman by making a get request to fetch student data from a sample api, validate status code 200 and the response data before automation.

Learn basic mouse actions—click, right-click, double-click—and keyboard operations with alphanumeric and special keys in Cypress test scenarios.