- Professional Development
- Medicine & Nursing
- Arts & Crafts
- Health & Wellbeing
- Personal Development
31 Data Science courses in London
Data Analysis and Visualization with Microsoft Excel
By Mpi Learning - Professional Learning And Development Provider
This course is designed for students who already have foundational knowledge and skills in Excel and who wish to perform robust and advanced data and statistical analysis with Microsoft Excel using PivotTables, use tools such as Power Pivot and the Data Analysis ToolPak to analyze data and visualize data and insights using advanced visualizations in charts and dashboards in Excel.
The “ISO 42001:2023 Lead Implementer Course” is designed to provide participants with the knowledge and skills necessary to lead the implementation of an Artificial Intelligence Management System based on ISO 42001:2023. This comprehensive course covers the key principles, requirements, and best practices for establishing and maintaining an effective Artificial Intelligence management system. Participants will learn how to develop, implement, and manage processes that comply with the ISO 42001 standard.
Python Basics: Course Description Excellent for beginners, practical, in small groups of max 4 people, 1 Day Online Instructor-led. You could contact us for your prefereed date. Session 1: Python Data Types and Variables: Primitive types; Characters & Strings; Boolean; Working with variables and its scope; Conversion and casting types in Python. Operators and Expressions: Introduction of operators; Arithmetic operators; Relational operators; Assignment operator; Logical operators; Increment and decrement operators.. Exercise: Calculate Movie Tickets for a Party, Are there enough seats in the cinema? Decision Making & Loops If statement; If - else statement; If- elif - else statement; Nested if - else; Exercise: Calculate the travel fee to deliver goods The while, For loop Jump statements: break, continue; Nesting loops. Exercise: Enter a password, if incorrect 3 times, you are blocked. Session 2: Data Structures Lists. Tuples. Exercise: Hangman Game Exercise: Get a word for the game from a Json File, store the high score in a Dictionary file Session 3: Files and exceptions Exception Handling, Exception types; Using try and Except. Files, streams: Open, Traverse, Read and Create Files: Csv, txt and Json Files. API: Connecting to API’s. Session 4: OOP Creating and using custom Functions. Using parameters and return values. Creating a Class; Creating an Object; Using an Object; Adding Instance variables; Class Constructors; Parameterized Constructors. Inheritance. Override. Session 5: Pandas Dataframe Basics Getting data into a dataframe: Dict to Dataframe, Dataframe to Dict. Excel To Dict, Dict to Excel , working with Excel data, multiple Excel sheets. Getting information about the dataframe, Filter, sort and query a Dataframes, Slicing Dataframes, Duplicate values,Working with null-values, Sampling. Exercise: Query the top 1000 grossing movies of the last century Session 6: Built in Functions: String, Math, Random Python built-in functions: Strings functions. Maths functions. Random Functions. Exercise: Find information in prose, to get the sentiment of the prose. Exercise: Get a word for the game from a txt File Exercise: Win the lottery Included: PCWorkshops's Python Programming Basics Certification Course notes, exercises and code examples Revision session after the course Refund Policy No Refunds
This Python Machine Learning online instructor led course is an excellent introduction to popular machine learning algorithms. Python Machine Learning 2-day Course Prerequisites: Basic knowledge of Python coding is a pre-requisite. Who Should Attend? This course is an overview of machine learning and machine learning algorithms in Python SciKitLearn. Practical: We cover the below listed algorithms, which is only a small collection of what is available. However, it will give you a good understanding, to plan your Machine Learning project We create, experiment and run machine learning sample code to implement a short selected but representative list of available the algorithms. Course Outline: Supervised Machine Learning: Classification Algorithms: Naive Bayes, Decision Tree, Logistic Regression, K-Nearest Neighbors, Support Vector Machine Regression Algorithms: Linear, Polynomial Unsupervised Machine Learning: Clustering Algorithms: K-means clustering, Hierarchical Clustering Dimension Reduction Algorithms: Principal Component Analysis Latent Dirichlet allocation (LDA) Association Machine Learning Algorithms: Apriori, Euclat Other machine learning Algorithms: Ensemble Methods ( Stacking, bagging, boosting ) Algorithms: Random Forest, Gradient Boosting Reinforcement learning Algorithms: Q-Learning Neural Networks and Deep Leaning Algorithms: Convolutional Network (CNN) Data Exploration and Preprocessing: The first part of a Machine Learning project understands the data and the problem at hand. Data cleaning, data transformation and data pre-processing are covered using Python functions to make data exploration and preprocessing relatively easy. What is included in this Python Machine Learning: Python Machine Learning Certificate on completion Python Machine Learning notes Practical Python Machine Learning exercises and code examples After the course, 1 free, online session for questions or revision Python Machine Learning. Max group size on this Python Machine Learning is 4. Refund Policy No Refunds
Certified Artificial Intelligence Practitioner
By Mpi Learning - Professional Learning And Development Provider
This course shows you how to apply various approaches and algorithms to solve business problems through AI and ML, follow a methodical workflow to develop sound solutions, use open-source, off-the-shelf tools to develop, test, and deploy those solutions, and ensure that they protect the privacy of users. This course includes hands-on activities for each topic area.
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.
Course summary This Python Programming course has become essential to all professional who would like to do code using Python. Learn evenings, work while studying. Work and study Python Part Time. It is a Python beginners course and teaches Python coding from scratch to intermediate. Hands-on, practical. We code some real life examples in this course.