Generative AI for Business Leaders
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How Google does Machine Learning
دوراتنا
Statistics Fundamentals Proctored Exam
Test your knowledge and ability to apply the concepts and methods from the four courses included in the LSE MicroBachelors program in Statistics Fundamentals and take your first step towards further study at undergraduate level or upskill in high-growth careers.
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Course by
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الإنجليزية
Statistics 2 Part 2: Statistical Inference
The final part in a series of four courses which help you to master statistics fundamentals and build your quantitative skillset for progression in high-growth careers, or to use as step towards further study at undergraduate level.
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Course by
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الإنجليزية
Statistics 2 Part 1: Probability and Distribution Theory
The third in a series of four courses which help you to master statistics fundamentals and build your quantitative skillset for progression in high-growth careers, or to use as step towards further study at undergraduate level.
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Course by
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الإنجليزية
Statistics 1 Part 2: Statistical Methods
The second in a series of four courses which help you to master statistics fundamentals and build your quantitative skillset for progression in high-growth careers, or to use as step towards further study at undergraduate level.
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Course by
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الإنجليزية
Statistics 1 Part 1: Introductory statistics, probability and estimation
The first in a series of four courses which help you to master statistics fundamentals and build your quantitative skillset for progression in high-growth careers, or to use as step towards further study at undergraduate level.
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Course by
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الإنجليزية
Mathematics and Statistics Fundamentals Proctored Exam
Test your knowledge and ability to apply the concepts and methods from the four courses included in the LSE MicroBachelors program in Mathematics and Statistics Fundamentals and take your first step towards further study at undergraduate level or upskill in high-growth careers.
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Course by
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الإنجليزية
Fat Chance: Probability from the Ground Up
Increase your quantitative reasoning skills through a deeper understanding of probability and statistics.
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Course by
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التعلم الذاتي
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30
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الإنجليزية
Machine Learning for Supply Chains
This specialization is intended for students who wish to use machine language to analyze and predict product usage and other similar tasks. There is no specific prerequisite but some general knowledge of supply chain will be helpful, as well as general statistics and calculus.
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Course by
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Self Paced
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الإنجليزية
Deep Learning and Reinforcement Learning
This course introduces you to two of the most sought-after disciplines in Machine Learning: Deep Learning and Reinforcement Learning. Deep Learning is a subset of Machine Learning that has applications in both Supervised and Unsupervised Learning, and is frequently used to power most of the AI applications that we use on a daily basis. First you will learn about the theory behind Neural Networks, which are the basis of Deep Learning, as well as several modern architectures of Deep Learning.
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Course by
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32 ساعات
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الإنجليزية
Data Science Methods for Quality Improvement
Data analysis skills are widely sought by employers, both nationally and internationally. This specialization is ideal for anyone interested in data analysis for improving quality and processes in business and industry. The skills taught in this specialization have been used extensively to improve business performance, quality, and reliability. By completing this specialization, you will improve your ability to analyze data and interpret results as well as gain new skills, such as using RStudio and RMarkdown.
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Course by
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Self Paced
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الإنجليزية
Business Analytics
Nowadays data is essential in the business environment to be gain a global view of an organization's situation and to be able to make better decisions. Against this background, Big Data is a booming sector in multiple areas that opens up different job opportunities, such as the role of Data Analyst. This course is an introduction to data analytics from a business perspective, focusing on the relevance of basing strategic decision-making on the knowledge provided by data.
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Course by
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الإنجليزية
Data Understanding and Visualization
The "Data Understanding and Visualization" course provides students with essential statistical concepts to comprehend and analyze datasets effectively. Participants will learn about central tendency, variation, location, correlation, and other fundamental statistical measures. Additionally, the course introduces data visualization techniques using Pandas, Matplotlib, and Seaborn packages, enabling students to present data visually with appropriate plots for accurate and efficient communication. Learning Objectives: 1.
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Course by
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25 ساعات
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الإنجليزية
Machine Learning for Trading
This 3-course Specialization from Google Cloud and New York Institute of Finance (NYIF) is for finance professionals, including but not limited to hedge fund traders, analysts, day traders, those involved in investment management or portfolio management, and anyone interested in gaining greater knowledge of how to construct effective trading strategies using Machine Learning (ML) and Python. Alternatively, this program can be for Machine Learning professionals who seek to apply their craft to quantitative trading strategies.
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Course by
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Self Paced
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الإنجليزية
Using R for Regression and Machine Learning in Investment
In this course, the instructor will discuss various uses of regression in investment problems, and she will extend the discussion to logistic, Lasso, and Ridge regressions. At the same time, the instructor will introduce various concepts of machine learning. You can consider this course as the first step toward using machine learning methodologies in solving investment problems. The course will cover investment analysis topics, but at the same time, make you practice it using R programming.
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Course by
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Self Paced
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18 ساعات
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الإنجليزية
Six Sigma Tools for Analyze
This course will cover the Measure phase and portions of the Analyze phase of the Six Sigma DMAIC (Define, Measure, Analyze, Improve, and Control) process. You will learn about lean tools for process analysis, failure mode and effects analysis (FMEA), measurement system analysis (MSA) and gauge repeatability and reproducibility (GR&R), and you will be introduced to basic statistics. This course will outline useful measure and analysis phase tools and will give you an overview of statistics as they are related to the Six Sigma process.
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Course by
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Self Paced
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8 ساعات
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الإنجليزية
Basic Statistics in Python (ANOVA)
In this 1-hour long project-based course, you will learn how to set up a Google Colab notebook, source data from the internet, load data into Python, merge two datasets, clean data, perform exploratory data analysis, carry out ANOVA and create boxplots.
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Course by
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Self Paced
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4 ساعات
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الإنجليزية
Vital Skills for Data Science
Vital Skills for Data Science introduces students to several areas that every data scientist should be familiar with. Each of the topics is a field in itself. This specialization provides a "taste" of each of these areas which will allow the student to determine if any of these areas is something they want to explore further. In this specialization, students will learn about different applications of data science and how to apply the steps in a data science process to real life data.
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Course by
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Self Paced
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الإنجليزية
Probability and Statistics IV: Confidence Intervals and Hypothesis Tests
This course covers two important methodologies in statistics – confidence intervals and hypothesis testing. Confidence intervals allow us to make probabilistic statements such as: “We are 95% sure that Candidate Smith’s popularity is 52% +/- 3%.” Hypothesis testing allows us to pose hypotheses and test their validity in a statistically rigorous way. For instance, “Does a new drug result in a higher cure rate than the old drug?"
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Course by
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الإنجليزية
Guided Tour of Machine Learning in Finance
This course aims at providing an introductory and broad overview of the field of ML with the focus on applications on Finance. Supervised Machine Learning methods are used in the capstone project to predict bank closures.
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Course by
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Self Paced
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24 ساعات
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الإنجليزية
Text Marketing Analytics
Marketing data are complex and have dimensions that make analysis difficult. Large unstructured datasets are often too big to extract qualitative insights. Marketing datasets also are relational and connected. This specialization tackles advanced advertising and marketing analytics through three advanced methods aimed at solving these problems: text classification, text topic modeling, and semantic network analysis. Each key area involves a deep dive into the leading computer science methods aimed at solving these methods using Python.
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Course by
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Self Paced
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الإنجليزية
Fundamentals of Data Analysis
This course is the first of a series that aims to prepare you for a role working in data analytics. In this course, you’ll be introduced to many of the primary types of data analytics and core concepts. You’ll learn about the tools and skills required to conduct data analysis. We’ll go through some of the foundational math and statistics used in data analysis and workflows for conducting efficient and effective data analytics.
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Course by
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Self Paced
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18 ساعات
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الإنجليزية
Machine Learning and Reinforcement Learning in Finance
The main goal of this specialization is to provide the knowledge and practical skills necessary to develop a strong foundation on core paradigms and algorithms of machine learning (ML), with a particular focus on applications of ML to various practical problems in Finance. The specialization aims at helping students to be able to solve practical ML-amenable problems that they may encounter in real life that include: (1) mapping the problem on a general landscape of available ML methods, (2) choosing particular ML approach(es) that would be most appropriate for resolving the problem, and (3
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Course by
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Self Paced
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الإنجليزية
How To Create Effective Metrics
By the end of this project, you will be able to create effective metrics for a business. You will learn what metrics are, how to create benchmarks, and how to build a system for sharing and evaluating metrics. Excel is a great tool to use if you have plans to adopt a data-driven approach to making business decisions. We will be sharpening our data analysis tools in Excel during this project.
This is a great tool to use if you have plans to use data, analytics, and or metrics to improve your business functions and decision making.
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Course by
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Self Paced
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2 ساعات
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الإنجليزية
Hypothesis Testing in R
Welcome to this project-based course Hypothesis Testing in R. In this project, you will learn how to perform extensive hypothesis tests for one and two samples in R.
By the end of this 2-hour long project, you will understand the rationale behind performing hypothesis testing. Also, you will learn how to perform hypothesis tests for proportions and means. By extension, you will learn how to perform a hypothesis test for means of matched or paired samples in R.
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Course by
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Self Paced
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3 ساعات
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الإنجليزية
Effective Communication Capstone Project
In the Effective Communication Capstone learners apply the lessons of Business Writing, Graphic Design, and Successful Presentation to create a portfolio of work that represents their mastery of writing, design, and speaking and that expresses their personal brand. The portfolio includes three individual elements—a written memo, a slide deck, and a presentation—integrated around a single topic. We provide the elements for a basic capstone, but we also invite our learners to create their own project if they so choose.
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Course by
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Self Paced
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14 ساعات
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الإنجليزية