31 Courses in London

The CAIA Association is a global professional body dedicated to creating greater alignment, transparency, and knowledge for all investors, with a specific emphasis on alternative investments. Course Overview The CAIA Association is a global professional body dedicated to creating greater alignment, transparency, and knowledge for all investors, with a specific emphasis on alternative investments. A Member-driven organization representing professionals in more than 100 countries, CAIA Association advocates for the highest ethical standards. Whether you need a deep, practical understanding of the world of alternative investments, a solid introduction, or data science skills for the future in finance, the CAIA Association offers a program for you. Why CAIA? Distinguish yourself with knowledge, expertise, and a clear career advantage – become a CAIA Charterholder. CAIA® is the globally recognized credential for professionals allocating, managing, analyzing, distributing, or regulating alternative investments. The Level II curriculum takes a top-down approach and provides Candidates with the skills and tools to conduct due diligence, monitor investments, and appropriately construct an investment portfolio. In addition, the Level II curriculum contains Emerging Topic readings; articles written by academics and practitioners designed to further inform and provoke the Candidate’s investment management process. After passing the Level II exam you are eligible, with relevant professional experience, to join the CAIA Association as a Member and receive the CAIA Charter. You will be part of an elite group of more than 13,000 professionals worldwide. Only after joining the Association, you are eligible to add the CAIA designation to your professional profiles. Who will benefit from enrolling in the CAIA program? Professionals who want to develop a deep level of knowledge and demonstrated expertise in alternative investments and their contribution to the diversified portfolio should pursue the CAIA Charter including: • Asset Allocators • Risk managers • Analysts • Portfolio managers • Traders • Consultants • Business development/marketing • Operations • Advisors Curriculum Topics: Topic 1: Emerging Topics • Decentralized Finance: On Blockchain- and Smart Contract-Based Financial Markets • Technical Guide for Limited Partners: Responsible Investing in Private Equity • Channels for Exposure to Bitcoin • Assessing Long-Term Investor Performance: Principles, Policies and Metrics • Demystifying Illiquid Assets: Expected Returns for Private Equity • An Introduction to Portfolio Rebalancing Strategies • Longevity and Liabilities: Bridging the Gap • A Short Introduction to the World of Cryptocurrencies Topic 2: Ethics, Regulation and ESG • Asset Manager Code • Recommendations and Guidance • Global Regulation • ESG and Alternative Investments • ESG Analysis and Application Topic 3: Models • Modeling Overview and Interest Rate Models • Credit Risk Models • Multi-Factor Equity Pricing Models • Asset Allocation Processes and the Mean-Variance Model • Other Asset Allocation Approaches Topic 4: Institutional Asset Owners and Investment Policies • Types of Asset Owners and the Investment Policy Statement • Foundations and the Endowment Model • Pension Fund Portfolio Management • Sovereign Wealth Funds • Family Offices and the family office Model Topic 5: Risk and Risk Management • Cases in Tail Risk • Benchmarking and Performance Attribution • Liquidity and Funding Risks • Hedging, Rebalancing, and Monitoring • Risk Measurement, Risk Management, and Risk Systems Topic 6: Methods for Alternative Investing • Valuation and Hedging Using Binomial Trees • Directional Strategies and Methods • Multivariate Empirical Methods and Performance Persistence • Relative Value Methods • Valuation Methods for Private Assets: The Case of Real Estate Topic 7: Accessing Alternative Investments • Hedge Fund Replication • Diversified Access to Hedge Funds • Access to Real Estate and Commodities • Access through Private Structures • The Risk and Performance of Private and Listed Assets Topic 8: Due Diligence and Selecting Managers • Active Management and New Investments • Selection of a Fund Manager • Investment Process Due Diligence • Operational Due Diligence • Due Diligence of Terms and Business Activities Topic 9: Volatility and Complex Strategies • Volatility as a Factor Exposure • Volatility, Correlation, and Dispersion Products and Strategies • Complexity and Structured Products • Insurance-Linked and Hybrid Securities • Complexity and the Case of Cross-Border Real Estate Investing DURATION 200 Hours WHATS INCLUDED Course Material Case Study Experienced Lecturer Refreshments Certificate

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.

The “ISO 42001:2023 Lead Auditor Course” integrates the principles of ISO 42001:2023, the International Standard for Artificial Intelligence Management, with the methodologies outlined in ISO 19011:2018, the Guidelines for Auditing Management Systems. The course equips participants with the skills and knowledge required to lead Artificial Intelligence audits effectively, ensuring compliance with ISO 42001:2023, and applies the principles of ISO 17011:2017 for conformity assessment bodies.

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.

Python Data Analytics boot camp. 12 1 day lessons, learn Python Basics through to machine learning and front-ends. With practical project to give you full confidence and credibility.

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

PYTHON BOOTCAMP: This 12-week Python Data Analytics Data Boot Camp is designed to give you a complete skill set required by data analysts . You will be fully fluent and confident as a Python data analyst, with full understanding of Python Programming. From Data, databases, datasets, importing, cleaning, transforming, analysing to visualisation and creating awesome dashboards The course is a practical, instructor-lead program.

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.

https://www.transmedia.co.uk/course/ai-image-generation-using-firefly