Generative AI for Business Leaders
Advertising with Meta
How Google does Machine Learning
دوراتنا
Applied Data Science with R
This Specialization is intended for anyone with a passion for learning who is seeking to develop the job-ready skills, tools, and portfolio to have a competitive edge in the job market as an entry-level data scientist. Through these five online courses, you will develop the skills you need to bring together often disparate and disconnected data sources and use the R programming language to transform data into insights that help you and your stakeholders make more informed decisions. By the end of this Specialization, you will be able to perform basic R programming tasks to complete the data
-
Course by
-
Self Paced
-
الإنجليزية
Data Science for Investment Professionals
This Specialization is uniquely tailored to the needs of investment professionals or those with investment industry knowledge who want to develop a basic, practical understanding of machine learning techniques and how th…
-
Course by
-
Self Paced
-
الإنجليزية
Business Statistics and Analysis
The Business Statistics and Analysis Specialization is designed to equip you with a basic understanding of business data analysis tools and techniques. Informed by our world-class Data Science master's and PhD course material, you’ll master essential spreadsheet functions, build descriptive business data measures, and develop your aptitude for data modeling. You’ll also explore basic probability concepts, including measuring and modeling uncertainty, and you’ll use various data distributions, along with the Linear Regression Model, to analyze and inform business decisions.
-
Course by
-
Self Paced
-
الإنجليزية
Applied Data Science with Python
The 5 courses in this University of Michigan specialization introduce learners to data science through the python programming language.
-
Course by
-
Self Paced
-
الإنجليزية
Investment Management with Python and Machine Learning
The Data Science and Machine Learning for Asset Management Specialization has been designed to deliver a broad and comprehensive introduction to modern methods in Investment Management, with a particular emphasis on the use of data science and machine learning techniques to improve investment decisions.By the end of this specialization, you will have acquired the tools required for making sound investment decisions, with an emphasis not only on the foundational theory and underlying concepts, but also on practical applications and implementation.
-
Course by
-
Self Paced
-
الإنجليزية
AI Product Management
Organizations in every industry are accelerating their use of artificial intelligence and machine learning to create innovative new products and systems. This requires professionals across a range of functions, not just strictly within the data science and data engineering teams, to understand when and how AI can be applied, to speak the language of data and analytics, and to be capable of working in cross-functional teams on machine learning projects. This Specialization provides a foundational understanding of how machine learning works and when and how it can be applied to solve problems.
-
Course by
-
Self Paced
-
الإنجليزية
Unsupervised Text Classification for Marketing Analytics
Marketing data is often so big that humans cannot read or analyze a representative sample of it to understand what insights might lie within. In this course, learners use unsupervised deep learning to train algorithms to extract topics and insights from text data. Learners walk through a conceptual overview of unsupervised machine learning and dive into real-world datasets through instructor-led tutorials in Python. The course concludes with a major project. This course uses Jupyter Notebooks and the coding environment Google Colab, a browser-based Jupyter notebook environment.
-
Course by
-
Self Paced
-
13 ساعات
-
الإنجليزية
Use Tableau for Your Data Science Workflow
Learn Tableau fundamentals, advanced visualizations, and integration with data science tools. Elevate your skills in creating impactful dashboards. Enroll now for hands-on experience and master the art of data storytelling. Unlock the potential for advanced analytics, exploring correlations and trends within your data. Build interactive dashboards that tell compelling data stories, utilizing filters, parameters, and actions for user engagement. Uplift your expertise with advanced visualizations, mastering heatmaps, tree maps, and geographical mapping.
-
Course by
-
Self Paced
-
الإنجليزية
Machine Learning: Theory and Hands-on Practice with Python
In the Machine Learning specialization, we will cover Supervised Learning, Unsupervised Learning, and the basics of Deep Learning. You will apply ML algorithms to real-world data, learn when to use which model and why, and improve the performance of your models. Starting with supervised learning, we will cover linear and logistic regression, KNN, Decision trees, ensembling methods such as Random Forest and Boosting, and kernel methods such as SVM. Then we turn our attention to unsupervised methods, including dimensionality reduction techniques (e.g., PCA), clustering, and recommender systems.
-
Course by
-
Self Paced
-
الإنجليزية
Data Science Foundations: Data Structures and Algorithms
Building fast and highly performant data science applications requires an intimate knowledge of how data can be organized in a computer and how to efficiently perform operations such as sorting, searching, and indexing. …
-
Course by
-
Self Paced
-
الإنجليزية
MLOps | Machine Learning Operations
This comprehensive course series is perfect for individuals with programming knowledge such as software developers, data scientists, and researchers. You'll acquire critical MLOps skills, including the use of Python and Rust, utilizing GitHub Copilot to enhance productivity, and leveraging platforms like Amazon SageMaker, Azure ML, and MLflow.
-
Course by
-
Self Paced
-
الإنجليزية
Statistical Learning for Data Science
Statistical Learning is a crucial specialization for those pursuing a career in data science or seeking to enhance their expertise in the field. This program builds upon your foundational knowledge of statistics and equips you with advanced techniques for model selection, including regression, classification, trees, SVM, unsupervised learning, splines, and resampling methods. Additionally, you will gain an in-depth understanding of coefficient estimation and interpretation, which will be valuable in explaining and justifying your models to clients and companies.
-
Course by
-
Self Paced
-
الإنجليزية
Software Architecture for Big Data
This specialization is for software engineers interested in the principles of building and architecting large software systems that use big data. Through three courses you will learn about how to build and architect performant distributed systems from industry experts at Initial Capacity. This specialization can be taken for academic credit as part of CU Boulder’s MS in Data Science or MS in Computer Science degrees offered on the Coursera platform. These fully accredited graduate degrees offer targeted courses, short 8-week sessions, and pay-as-you-go tuition.
-
Course by
-
Self Paced
-
الإنجليزية
Executive Data Science
Assemble the right team, ask the right questions, and avoid the mistakes that derail data science projects. In four intensive courses, you will learn what you need to know to begin assembling and leading a data science enterprise, even if you have never worked in data science before. You’ll get a crash course in data science so that you’ll be conversant in the field and understand your role as a leader. You’ll also learn how to recruit, assemble, evaluate, and develop a team with complementary skill sets and roles.
-
Course by
-
Self Paced
-
الإنجليزية
Mastering Software Development in R
R is a programming language and a free software environment for statistical computing and graphics, widely used by data analysts, data scientists and statisticians. This Specialization covers R software development for building data science tools.
-
Course by
-
Self Paced
-
الإنجليزية
Genomic Data Science
With genomics sparks a revolution in medical discoveries, it becomes imperative to be able to better understand the genome, and be able to leverage the data and information from genomic datasets. Genomic Data Science is the field that applies statistics and data science to the genome. This Specialization covers the concepts and tools to understand, analyze, and interpret data from next generation sequencing experiments.
-
Course by
-
Self Paced
-
الإنجليزية
IBM Data Science
Prepare for a career in the high-growth field of data science. In this program, you’ll develop the skills, tools, and portfolio to have a competitive edge in the job market as an entry-level data scientist in as little as 4 months. No prior knowledge of computer science or programming languages is required. Data science involves gathering, cleaning, organizing, and analyzing data with the goal of extracting helpful insights and predicting expected outcomes.
-
Course by
-
Self Paced
-
الإنجليزية
Data Science with R - Capstone Project
In this capstone course, you will apply various data science skills and techniques that you have learned as part of the previous courses in the IBM Data Science with R Specialization or IBM Data Analytics with Excel and R Professional Certificate. For this project, you will assume the role of a Data Scientist who has recently joined an organization and be presented with a challenge that requires data collection, analysis, basic hypothesis testing, visualization, and modeling to be performed on real-world datasets.
-
Course by
-
Self Paced
-
26 ساعات
-
الإنجليزية
Applications of Software Architecture for Big Data
The course is intended for individuals who want to build a production-quality software system that leverages big data. You will apply the basics of software engineering and architecture to create a production-ready distributed system that handles big data. You will build data intensive, distributed system, composed of loosely coupled, highly cohesive applications. This course can be taken for academic credit as part of CU Boulder’s MS in Data Science or MS in Computer Science degrees offered on the Coursera platform.
-
Course by
-
Self Paced
-
34 ساعات
-
الإنجليزية
Statistical Modeling for Data Science Applications
Statistical modeling lies at the heart of data science. Well crafted statistical models allow data scientists to draw conclusions about the world from the limited information present in their data. In this three credit sequence, learners will add some intermediate and advanced statistical modeling techniques to their data science toolkit. In particular, learners will become proficient in the theory and application of linear regression analysis; ANOVA and experimental design; and generalized linear and additive models.
-
Course by
-
Self Paced
-
الإنجليزية
Tidyverse Skills for Data Science in R
This Specialization is intended for data scientists with some familiarity with the R programming language who are seeking to do data science using the Tidyverse family of packages. Through 5 courses, you will cover importing, wrangling, visualizing, and modeling data using the powerful Tidyverse framework. The Tidyverse packages provide a simple but powerful approach to data science which scales from the most basic analyses to massive data deployments. This course covers the entire life cycle of a data science project and presents specific tidy tools for each stage.
-
Course by
-
Self Paced
-
الإنجليزية
Data Mining Foundations and Practice
The Data Mining specialization is intended for data science professionals and domain experts who want to learn the fundamental concepts and core techniques for discovering patterns in large-scale data sets.
-
Course by
-
Self Paced
-
الإنجليزية
Data Science
Ask the right questions, manipulate data sets, and create visualizations to communicate results. This Specialization covers the concepts and tools you'll need throughout the entire data science pipeline, from asking the right kinds of questions to making inferences and publishing results. In the final Capstone Project, you’ll apply the skills learned by building a data product using real-world data. At completion, students will have a portfolio demonstrating their mastery of the material.
-
Course by
-
Self Paced
-
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.
-
Course by
-
Self Paced
-
الإنجليزية
Data Science with Databricks for Data Analysts
This specialization is intended for data analysts looking to expand their toolbox for working with data. Traditionally, data analysts have used tools like relational databases, CSV files, and SQL programming, among other…
-
Course by
-
Self Paced
-
الإنجليزية