Overview
Understand the fundamentals of software testing, its importance, and its role in the software development process., Learn Python programming basics, including variables, data types, control structures, and functions, with a focus on their relevance to testing., Explore unit testing concepts and frameworks (e.g., unittest, pytest) in Python., Write and execute unit tests to ensure individual code components work correctly., Dive into advanced testing topics like integration testing, end-to-end testing, and performance testing.
Software Testers: Individuals working in software testing who want to improve their Python programming skills for test automation., Software Developers: Developers interested in test-driven development (TDD) and writing high-quality code through testing., Students and Aspiring Developers: Students or aspiring developers looking to gain practical experience in test development as part of their Python learning journey., Automation Engineers: Professionals involved in automation who want to leverage Python for creating automated test scripts., Freelancers and Consultants: Freelancers and consultants in the software industry who want to expand their skill set and offer Python test development services.
Basic Python Proficiency: Participants should have a solid understanding of Python programming fundamentals, including variables, data types, loops, and functions., Intermediate Python Skills: A prerequisite may include familiarity with more advanced Python concepts like object-oriented programming (OOP), libraries/modules, and exception handling., Understanding of Software Testing: Participants should have a grasp of software testing concepts, including unit testing, integration testing, and test-driven development (TDD)., Command-Line Proficiency: A basic understanding of the command line and how to run Python scripts from the terminal or command prompt.
Are you ready to become a proficient Python test developer, capable of ensuring the reliability and quality of your software projects from start to finish? If so, then this comprehensive course is your gateway to mastering the art of test development using Python, taking you from the very basics to advanced levels.
Course Highlights:
1. Python Fundamentals for Testing: Begin your journey by establishing a solid foundation in Python programming. You'll learn the syntax, data structures, and essential concepts required for effective test development.
2. Understanding Testing Principles: Explore the fundamental principles of software testing, including test-driven development (TDD), unit testing, integration testing, and more. Gain insights into the importance of testing in the software development life-cycle.
3. Writing Unit Tests: Dive into the world of unit testing with Python's built-in testing framework, unit test. You'll learn how to write and execute unit tests, test fixtures, and test cases to ensure the correctness of individual code components.
4. Test Automation: Discover the power of test automation. Learn how to create automated test suites that can be run repeatedly to validate your code's functionality and catch regressions.
5. Advanced Testing Techniques: Take your testing skills to the next level by exploring advanced testing techniques such as mocking, test doubles, and parameterized testing. Learn how to test complex scenarios and edge cases effectively.
6. Web Testing with Selenium: Extend your testing expertise to web applications. You'll gain hands-on experience with Selenium, a popular Python library for automating web browser interactions and testing web applications.
7. Test Frameworks and Best Practices: Explore popular testing frameworks like testes and nose, and discover best practices for organizing and structuring your test code to ensure maintainability and scalability.
8. Continuous Integration (CI) and Continuous Testing: Learn how to integrate your tests into a CI/CD pipeline, automating the testing process whenever code changes are made. You'll ensure that your software remains reliable as it evolves.
9. Real-World Projects: Apply your knowledge through practical, real-world projects and exercises. You'll work on a variety of testing scenarios and gain hands-on experience in solving common testing challenges.
10. Test Reporting and Analysis: Learn how to generate meaningful test reports and analyze test results to make informed decisions about code quality and improvements.
Akhil Vydyula
Hello, I'm Akhil, an Associate Consultant at Atos India with a focus on the Advisory Consulting practice, specializing in Data and Analytics. My professional journey has led me through various facets of data analysis and modeling, particularly in the BFSI sector, where I've had the privilege of overseeing the full lifecycle of development and execution.
My skill set encompasses a wide range of data-related tasks, including data wrangling, feature engineering, algorithm development, model training, and implementation. I thrive on leveraging data mining techniques such as statistical analysis, hypothesis testing, regression analysis, as well as both unsupervised and supervised machine learning processes to extract meaningful insights and drive data-informed decisions. I'm particularly passionate about risk identification through decision models, and I've honed my expertise in Machine Learning Algorithms, Data/Text Mining techniques, and Data Visualization to effectively address these challenges.
Currently, I'm immersed in an exciting Amazon cloud project that involves end-to-end development of ETL processing. In this role, I craft ETL processing code using PySpark/Spark SQL to extract data from S3 buckets, perform necessary transformations, execute scripts using EMR services, and load consolidated data into Postgres SQL (RDS/Redshift) on a full, incremental, and live basis. To streamline this process, I've automated it by creating jobs in Step functions, which trigger EMR instances to run scripts in a specific order and send notifications upon execution status changes. The scheduling of these Step functions is achieved through event bridge rules.
Additionally, I've worked extensively with AWS Glue, using it to replicate source data from on-premises systems to raw-layer S3 buckets via AWS DMS services. One of my key strengths lies in my ability to understand the nuances of data and apply the right transformations to convert data from multiple tables into key-value pairs. Furthermore, I've optimized the performance of stored procedures in Postgres SQL to execute second-level transformations by efficiently joining multiple tables and loading the data into final tables.
I'm passionate about harnessing the power of data to drive actionable insights and improve business outcomes. If you share this passion or are interested in collaborating on data-driven projects, feel free to connect with me. Let's explore the endless possibilities that data analytics has to offer!