Python Programming from Scratch with MySQL Database is a beginner-friendly course designed to teach you everything you need to know to start with Python programming and MySQL databases. Using these powerful tools, you'll learn how to build dynamic web applications and websites.
This course is a perfect supplement for ML enthusiasts. If you are only just beginning your adventures in machine learning and want to know the basics of statistics and regression used for machine learning, then go for it. Discover how you can level up and gain confidence to implement statistical methods and regression in machine learning with Python.
If you are someone with a background in Python programming and is interested in presenting your analysis in interactive web-based dashboards, then you are in the right place. This course primarily focuses on Dash, along with other key data science libraries, including Pandas and Plotly. Learn to use Dash and Plotly in Python which can help you to visualize your critical insights and KPIs in web apps that are easily sharable.
This course will help you get started with automation testing of web applications. You will cover the basic and advanced topics of Selenium and Python, along with unit tests, pytest, cross-browser testing, logging infrastructure, automation framework design, Jenkins, and a lot more.
Gain a thorough grasp of time series analysis and its effects, as well as practical tips on how to apply machine learning methods and build RNNs. Learn to train RNNs efficiently while taking crucial concepts such as overfitting and underfitting into account. The course offers a useful, hands-on manner for learning Python methods and principles.
This course is designed around three main activities for getting better results with deep learning models: better or faster learning, better generalization to new data, and better predictions when using final models. Take this course if you're passionate about deep learning with a solid foundation in this space and want to learn how to squeeze the best performance out of your deep learning models.
This course takes you through the concepts of object-oriented programming (OOP) and shows you how to use them for writing flawless Python programs.