Artificial Intelligence (AI) & Machine Learning (ML) are transforming multiple sectors of the economy, and impacting several aspects of our daily lives. As AI continues to pervade our world, it is becoming more and more critical to validate these types of systems.
In other words, AI needs Testing.
Over the last decades, there has been a spike in the trend for “AI driven testing”. AI & ML is already altering the landscape of testing. This aims the software testing to make Testing smarter and more efficient.
To be precise, Testers Need AI now.
Hence, we at Agile Testing Alliance are proud to announce you the launch of our training program on Artificial Intelligence.
AI for Software Testing ( Practical AI Program for Testers)
The program will help the testers with knowledge of developing a ML model and also test it. During the course we also cover both the sides of wall
1. AI in Testing – How can AI help in making software testing effective & reliable?
2. Testing in AI – How testers can test an AI model and make it more functional & resilient?
Course Duration : 2 Days
Date : 31st July, 1st Aug 2021
Days : Saturday and Sunday
Day 0 (30th July) - 7:00 pm to 8:00 pm (IST)
Day 1 and Day 2 (31st July, 1st Aug) - 2:00 pm to 9:00 pm (IST)
AI for Software Testing Training program will be a two day course covering the below topics and Lab session
Day 0 : 60 minutes
1. Setting up of python.
2. Basics of python programming.
3. Recap of mathematical formulas
Day 1 : 5 Sessions, 360 minutes
Session 1 : Introduction - 30 minutes
1. What is Artificial Intelligence?
2. What is Machine Learning?
3. What is Deep Learning?
4. What is Data Science?
5. Why do we Need AI in Software Testing?
6. Role of AI in testing
7. Applications of AI in testing
Session 2 : Data Analysis - 90 minutes
1. Data Processing
2. ETL of Data
3. Visualize the data
4. Activity on Data Analysis
Session 3 : Machine learning Algorithms - 120 minutes
1. Introduction to Machine learning Algorithms
2. Supervised learning - Classification and Regression
3. Unsupervised learning - Clustering and Association
Session 4 : Developing ML model [ Lab session ] - 120 minutes
1. Develop a ML regression model for predicting Tesla Stock price
2. Develop a ML classifier model for twitter sentiment analysis
Day 2 : 4 Sessions, 360 minutes
Session 5 : Testing in AI - 30 minutes
1. Introduction to Testing in AI
2. Why to test AI ?
3. Challenges and problems for Testing in AI
4. Key Strategies for implementing “Testing in AI”
Session 6 : Testing ML models [ Lab session ] - 150 minutes
1. White box testing in ML model
2. Black box testing in ML model
Session 7 : AI in Testing - 30 minutes
1. Introduction to AI in Testing
2. Where to apply AI in STLC
3. Talk about AI in testing use cases
4. Challenges for using AI in Testing
5. Key Strategies for implementing “AI in Testing”
Session 8 : Develop ML models for Testing - 120 minutes
1. Develop a model for Test Defect prediction
2. Develop a model for Defect Classification and Analysis
Am I Eligible?
Since the course not only covers testing but also basic development of Models, anyone with zero knowledge on programming and basic knowledge in testing can attend this program.