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Processing big data in real time is challenging due to scalability, information inconsistency, and fault tolerance. Big Data Analysis with Python teaches you how to use tools that can control this data avalanche for you. In this course, you’ll learn practical techniques to aggregate data into useful dimensions for posterior analysis, extract statistical measurements, and transform datasets into features for other systems.
Data Science Projects with Python training course is designed to give you practical guidance on industry-standard data analysis and machine learning tools in Python, with the help of realistic data. The course will help you understand how you can use pandas and Matplotlib to critically examine a dataset with summary statistics and graphs, and extract the insights you seek to derive. You will continue to build on your knowledge as you learn how to prepare data and feed it to machine learning algorithms, such as regularized logistic regression and random forest, using the scikit-learn package. You’ll discover how to tune the algorithms to provide the best predictions on new and, unseen data.
Upcoming schedule: Live Online, Tuesday 21 April 2020 at 09:00 to Thursday 23 April 2020 at 17:00 - (Duration: 3 days)
Python is a powerful and popular object-oriented programming/scripting language with many high quality libraries. This Introduction to Python 3 training course provides a comprehensive introduction to the core syntax and functions provided by Python, including coverage of its object-oriented and functional programming features. The course also explores the Python standard library.
This Data Wrangling with Python training course starts with the absolute basics of Python, focusing mainly on data structures. It then delves into the fundamental tools of data wrangling like NumPy and Pandas libraries. You’ll explore useful insights into why you should stay away from traditional ways of data cleaning, as done in other languages, and take advantage of the specialized pre-built routines in Python. This combination of Python tips and tricks will also demonstrate how to use the same Python backend and extract/transform data from an array of sources including the Internet, large database vaults, and Excel financial tables. To help you prepare for more challenging scenarios, you’ll cover how to handle missing or wrong data, and reformat it based on the requirements from the downstream analytics tool. The course will further help you grasp concepts through real-world examples and datasets.
This Advanced Python Development training course aims to extend and solidify your Python experience by exploring structural techniques and common Python APIs. You'll learn how to write OO and functional code, define and consume REST services and web sockets, implement multithreaded code, use popular Python data science libraries, implement Big Data solutions, and more.
This Automating with Python training course entitled Automation with Python will teach you how to create Python programs to:
The Advanced Python 3 training course aims to take attendees beyond basic Python.
The course will enable attendees to enable to produce more efficient, safer and maintainable code using standard Python idioms.
The course assumes you are happy with core Python concepts and syntax.
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Learn about the theoretical and practical aspects of using Python in the realm of Data Science, Business Analytics, and Data Logistics
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Python is a powerful and popular object-oriented programming/scripting language with many high quality libraries.
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