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You will learn how to add, subtract, multiply and divide fractions. PREVIOUS KNOWLEDGE NEEDED: Basic addition, subtraction and multiplication.

In this online course, you will learn how to solve simultaneous equations from start to finish using two algebraic methods. UNDERLYING KNOWLEDGE: Rearranging equations; Expanding brackets; Collecting like terms

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A 10 week SATs Success course for students in year 6. Tutoring in English and Tutoring in Maths in a small group year 6 tutor session.

Python Machine Learning algorithms can derive trends (learn) from data and make predictions on data by extrapolating on existing trends. Companies can take advantage of this to gain insights and ultimately improve business. Using Python Machine Learning scikit-learn, practice how to use Python Machine Learning algorithms to perform predictions on data. Learn the below listed algorithms, a small collection of available Python Machine Learning algorithms.

Forget your fear of all things finance, quickly understand financial terms and techniques and make a more calculated contribution in your management role.

Low cost maths tuition

Python Data Analytics with Python using Numpy, Pandas, Dataframes. Most attendees are in-work Data Professional. Private individuals are very welcome. Our Style: Hands-on, Practical Location: Online, Instructor-led

I cover a range of subjects, including mathematics, English and science, as well as targeted preparation for entrance exams such as the 11 plus, ISEB, and more. Additionally, I provide focused support for verbal reasoning and non-verbal reasoning assessments. Importantly, all tuition is bespoke, tailored to your child's unique learning needs and requirements. My goal is to offer comprehensive assistance tailored to the primary education curriculum and specific entrance requirements. I also support children in their transition to secondary school through secondary private tuition and GCSE private tuition in certain subjects. I can always recommend excellent private tutors if I am not able to support a particular subject, so get in touch!

Duration 3 Days 18 CPD hours This course is intended for Data Wrangling with Python takes a practical approach to equip beginners with the most essential data analysis tools in the shortest possible time. It contains multiple activities that use real-life business scenarios for you to practice and apply your new skills in a highly relevant context. Overview By the end of this course, you will be confident in using a diverse array of sources to extract, clean, transform, and format your data efficiently. In this course you will start with the absolute basics of Python, focusing mainly on data structures. Then you will delve 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. Introduction to Data Structure using Python Python for Data Wrangling Lists, Sets, Strings, Tuples, and Dictionaries Advanced Operations on Built-In Data Structure Advanced Data Structures Basic File Operations in Python Introduction to NumPy, Pandas, and Matplotlib NumPy Arrays Pandas DataFrames Statistics and Visualization with NumPy and Pandas Using NumPy and Pandas to Calculate Basic Descriptive Statistics on the DataFrame Deep Dive into Data Wrangling with Python Subsetting, Filtering, and Grouping Detecting Outliers and Handling Missing Values Concatenating, Merging, and Joining Useful Methods of Pandas Get Comfortable with a Different Kind of Data Sources Reading Data from Different Text-Based (and Non-Text-Based) Sources Introduction to BeautifulSoup4 and Web Page Parsing Learning the Hidden Secrets of Data Wrangling Advanced List Comprehension and the zip Function Data Formatting Advanced Web Scraping and Data Gathering Basics of Web Scraping and BeautifulSoup libraries Reading Data from XML RDBMS and SQL Refresher of RDBMS and SQL Using an RDBMS (MySQL/PostgreSQL/SQLite) Application in real life and Conclusion of course Applying Your Knowledge to a Real-life Data Wrangling Task An Extension to Data Wrangling