Coursera Courses |
|
Dasar-dasar Desain Pengalaman Pengguna (User Experience, UX) (Coursera) https://www.coursera.org/learn/dasar-dasar-desian-pengalaman-pengguna-ux Dasar-dasar Desain Pengalaman Pengguna (User Experience, UX) adalah bagian pertama dari tujuh rangkaian materi yang akan membekali Anda keterampilan yang berguna untuk melamar pekerjaan desain UX tingkat pemula. Desainer UX fokus pada interaksi orang-orang dengan berbagai produk seperti situs web, aplikasi mobile dan obyek fisik. Desainer UX menjadikan interaksi sehari-hari bermanfaat, menyenangkan, dan mudah diakses. Peran seorang desainer UX tingkat pemula meliputi: berempati dengan pengguna, |
|
Dasar-Dasar Dukungan Teknis (Coursera) https://www.coursera.org/learn/dasar-dasar-dukungan-teknis Materi ini adalah rangkaian pertama dari keseluruhan program pelatihan yang akan membantu Anda untuk berperan sebagai IT Support Specialist tingkat pemula. Dalam kursus ini, Anda akan diperkenalkan ke dunia Teknologi Informasi, atau IT. Anda akan mempelajari berbagai aspek Teknologi Informasi, seperti perangkat keras komputer, Internet, perangkat lunak komputer, pemecahan masalah, dan layanan pelanggan. Pelatihan ini mencakup berbagai topik dalam dunia IT yang dirancang untuk memberi Anda gambar |
|
Dasar-dasar Manajemen Proyek (Coursera) https://www.coursera.org/learn/dasar-dasar-manajemen-proyek Materi ini adalah yang pertama dari enam seri yang akan membekali Anda dengan keterampilan yang dibutuhkan untuk diterapkan pada posisi tingkat pemula di bidang manajemen proyek. Manajer proyek memegang peran kunci dalam memimpin, merencanakan, dan mengimplementasikan proyek penting untuk membantu keberhasilan organisasi mereka. Dalam materi ini, Anda akan menemukan terminologi dasar tentang manajemen proyek dan mendapatkan pemahaman yang lebih dalam tentang peran dan tanggung jawab seorang man |
|
Data & Cybersecurity (Coursera) https://www.coursera.org/learn/data-cybersecurity Como integrantes del mundo empresarial, los especialistas en el tratamiento de datos suelen ser uno de los principales objetivos de un ciberataque, ya que tienen acceso a información confidencial de una empresa. Aunque sean conocedores de los riesgos a los que están sometidas las organizaciones en las que trabajan, es importante tener un amplio y consolidado conocimiento en materia de ciberseguridad para poder prevenir los ataques; y en el caso de que ocurran, mitigar los riesgos que afecten a l |
|
Data Analysis and Interpretation Capstone (Coursera) https://www.coursera.org/learn/data-analysis-capstone The Capstone project will allow you to continue to apply and refine the data analytic techniques learned from the previous courses in the Specialization to address an important issue in society. You will use real world data to complete a project with our industry and academic partners. For example, you can work with our industry partner, DRIVENDATA, to help them solve some of the world's biggest social challenges! DRIVENDATA at www.drivendata.org, is committed to bringing cutting-edge practices |
|
Data Analysis and Presentation Skills: the PwC Approach Final Project (Coursera) https://www.coursera.org/learn/data-analysis-project-pwc In this Capstone Project, you'll bring together all the new skills and insights you've learned through the four courses. You'll be given a 'mock' client problem and a data set. You'll need to analyze the data to gain business insights, research the client's domain area, and create recommendations. You'll then need to visualize the data in a client-facing presentation. You'll bring it all together in a recorded video presentation. This course was created by PricewaterhouseCoopers LLP with an add |
|
Data Analysis and Reporting in SAS Visual Analytics (Coursera) https://www.coursera.org/learn/data-analysis-reporting-sas-va In this course, you learn how to use SAS Visual Analytics on SAS Viya to modify data for analysis, perform data discovery and analysis, and create interactive reports. |
|
Data Analysis and Representation, Selection and Iteration (Coursera) https://www.coursera.org/learn/data-analysis-representation-selection-iteration This course is the second course in the specialization exploring both computational thinking and beginning C programming. Rather than trying to define computational thinking, we’ll just say it’s a problem-solving process that includes lots of different components. Most people have a better understanding of what beginning C programming means! This course assumes you have the prerequisite knowledge from the previous course in the specialization. You should make sure you have that knowledge, eithe |
|
Data Analysis and Visualization with Power BI (Coursera) https://www.coursera.org/learn/data-analysis-and-visualization-with-power-bi This course forms part of the Microsoft Power BI Analyst Professional Certificate. This Professional Certificate consists of a series of courses that offers a good starting point for a career in data analysis using Microsoft Power BI. In this course, you will learn report design and formatting in Power BI, which offers extraordinary visuals for building reports and dashboards. Additionally, you will learn how to use report navigation to tell a compelling, data-driven story in Power BI. You will |
|
Data Analysis in Python with pandas & matplotlib in Spyder (Coursera) https://www.coursera.org/learn/codio-data-analysis-in-python-with-pandas-and-matplotlib-in-spyder Code and run your first Python script in minutes without installing anything! This course is designed for learners with no coding experience, providing a crash course in Python, which enables the learners to delve into core data analysis topics that can be transferred to other languages. In this course, you will learn how to import and organize your data, use functions to gather descriptive statistics, and perform statistical tests. To allow for a truly hands-on, self-paced learning experience |
|
Data Analysis in R with RStudio & Tidyverse (Coursera) https://www.coursera.org/learn/codio-data-analysis-in-r-with-rstudio-and-tidyverse Code and run your first R program in minutes without installing anything! This course is designed for learners with no prior coding experience, providing foundational knowledge of data analysis in R. The modules in this course cover descriptive statistics, importing and wrangling data, and using statistical tests to compare populations and describe relationships. This course presents examples in R using the industry-standard Integrated Development Environment (IDE) RStudio. To allow for a trul |
|
Data Analysis Tools (Coursera) https://www.coursera.org/learn/data-analysis-tools In this course, you will develop and test hypotheses about your data. You will learn a variety of statistical tests, as well as strategies to know how to apply the appropriate one to your specific data and question. Using your choice of two powerful statistical software packages (SAS or Python), you will explore ANOVA, Chi-Square, and Pearson correlation analysis. This course will guide you through basic statistical principles to give you the tools to answer questions you have developed. Through |
|
Data Analysis with Python (Coursera) https://www.coursera.org/learn/data-analysis-with-python Analyzing data with Python is an essential skill for Data Scientists and Data Analysts. This course will take you from the basics of data analysis with Python to building and evaluating data models. Topics covered include: - collecting and importing data - cleaning, preparing & formatting data - data frame manipulation - summarizing data - building machine learning regression models - model refinement - creating data pipelines You will learn how to import data from multiple sources |
|
Data Analysis with R Programming (Coursera) https://www.coursera.org/learn/data-analysis-r This course is the seventh course in the Google Data Analytics Certificate. In this course, you’ll learn about the programming language known as R. You’ll find out how to use RStudio, the environment that allows you to work with R, and the software applications and tools that are unique to R, such as R packages. You’ll discover how R lets you clean, organize, analyze, visualize, and report data in new and more powerful ways. Current Google data analysts will continue to instruct and provide you |
|
Data Analysis with Spreadsheets and SQL (Coursera) https://www.coursera.org/learn/data-analysis-with-spreadsheets-and-sql This course introduces you to how to use spreadsheets and SQL queries to analyze and extract data. You will learn how to practically apply the OSEMN data analysis framework and spreadsheet functions to clean data, calculate summary statistics, evaluate correlations, and more. You’ll also dive into common data visualization techniques and learn how to use dashboards to tell a story with your data. By the end of this course you will be able to: • Clean data with spreadsheets • Use common spreadsh |
|
Data Analysis with Tableau (Coursera) https://www.coursera.org/learn/data-analysis-with-tableau-public The Data Analysis with Tableau Course will teach you how to manipulate and prepare data for analysis and reporting. You will also learn how to use the analytics features in Tableau to more effectively calculate analytics versus manual calculations. In this course, you will perform exploratory data analysis as well as create reports using descriptive statistics and visualizations. This course is for anyone who is curious about entry-level roles that demand fundamental Tableau skills, such as bu |
|
Data Analyst Career Guide and Interview Preparation (Coursera) https://www.coursera.org/learn/career-guide-and-interview-prep-for-data-analyst-pc Data analytics professionals are in high demand around the world, and the trend shows no sign of slowing. There are lots of great jobs available, but lots of great candidates too. How can you get the edge in such a competitive field? This course will prepare you to enter the job market as a great candidate for a data analyst position. It provides practical techniques for creating essential job-seeking materials such as a resume and a portfolio, as well as auxiliary tools like a cover letter and |
|
Data Analytics for Lean Six Sigma (Coursera) https://www.coursera.org/learn/data-analytics-for-lean-six-sigma Welcome to this course on Data Analytics for Lean Six Sigma. In this course you will learn data analytics techniques that are typically useful within Lean Six Sigma improvement projects. At the end of this course you are able to analyse and interpret data gathered within such a project. You will be able to use Minitab to analyse the data. I will also briefly explain what Lean Six Sigma is. I will emphasize on use of data analytics tools and the interpretation of the outcome. I will use many d |
|
Data Analytics Foundations for Accountancy I (Coursera) https://www.coursera.org/learn/data-analytics-accountancy-1 Welcome to Data Analytics Foundations for Accountancy I! You’re joining thousands of learners currently enrolled in the course. I'm excited to have you in the class and look forward to your contributions to the learning community. To begin, I recommend taking a few minutes to explore the course site. Review the material we’ll cover each week, and preview the assignments you’ll need to complete to pass the course. Click Discussions to see forums where you can discuss the course material with fel |
|
Data Analytics Foundations for Accountancy II (Coursera) https://www.coursera.org/learn/data-analytics-accountancy-2 Welcome to Data Analytics Foundations for Accountancy II! I'm excited to have you in the class and look forward to your contributions to the learning community. To begin, I recommend taking a few minutes to explore the course site. Review the material we’ll cover each week, and preview the assignments you’ll need to complete to pass the course. Click Discussions to see forums where you can discuss the course material with fellow students taking the class. If you have questions about course co |
|
Data Analytics in Sports Law and Team Management (Coursera) https://www.coursera.org/learn/data-analytics-in-sports-law-and-team-management This course provides an introduction to the fundamental ideas in applying data analytics to issues surrounding key regulatory and management functions within the sports industry. Sports as an industry is increasingly relying on data analytics for more effective deployment of resources and assessment of performance in areas ranging from player productivity to fan engagement, talent identification and development, coaching, sponsorship, and marketing. This course and its successors will help you u |
|
Data Analytics Methods for Marketing (Coursera) https://www.coursera.org/learn/data-analytics-methods-for-marketing This course explores common analytics methods used by marketers such as audience segmentation, clustering and marketing mix modeling. . You'll explore how to use linear regression for marketing planning and forecasting, and how to assess advertising effectiveness through experiments. By the end of this course you will be able to: • Understand your audience using analytics and variable descriptions • Define a target audience using segmentation with K-means clustering • Use historical data to p |
|
Data and Health Indicators in Public Health Practice (Coursera) https://www.coursera.org/learn/data-public-health Epidemiology is often described as the cornerstone science in public health. Epidemiology in public health practice uses study design and analyses to identify causes in an outbreak situation, guides interventions to improve population health, and evaluates programs and policies. In this course, we'll define the role of the professional epidemiologist as it relates to public health services, functions, and competencies. With that foundation in mind, we'll introduce you to the problem solving met |
|
Data and Urban Governance (Coursera) https://www.coursera.org/learn/data-urban-governance Since the beginning of the 2000s, cities have witnessed a massive influx of data, transforming how cities are governed. Data has an impact on how city life is structured, as it influences coalitions, actors, instruments, policies, and forms of regulation. In this MOOC, we will look at this shift more closely: what has the advent of big data done to urban governance? Have platforms disrupted local authorities? How has big data changed local politics? How do we govern using algorithms? What is th |
|
Data Collection and Processing with Python (Coursera) https://www.coursera.org/learn/data-collection-processing-python This course teaches you to fetch and process data from services on the Internet. It covers Python list comprehensions and provides opportunities to practice extracting from and processing deeply nested data. You'll also learn how to use the Python requests module to interact with REST APIs and what to look for in documentation of those APIs. For the final project, you will construct a “tag recommender” for the flickr photo sharing site. The course is well-suited for you if you have already take |
|
Data Collection: Online, Telephone and Face-to-face (Coursera) https://www.coursera.org/learn/data-collection-methods This course presents research conducted to increase our understanding of how data collection decisions affect survey errors. This is not a “how–to-do-it” course on data collection, but instead reviews the literature on survey design decisions and data quality in order to sensitize learners to how alternative survey designs might impact the data obtained from those surveys. The course reviews a range of survey data collection methods that are both interview-based (face-to-face and telephone) and |
|
https://www.coursera.org/learn/data-ecosystem The Data Ecosystem course will give you a foundational understanding of the entire data ecosystem, including data management. Specifically, this course shows how a business intelligence analyst would organize, access, and use data. You will learn about a variety of data sources along with the use and purpose of each type. Additionally, you’ll learn about the importance of data quality and data governance in relation to effective data management. You’ll also learn about the goals of data manageme |
|
Data Engineering Capstone Project (Coursera) https://www.coursera.org/learn/data-enginering-capstone-project Showcase your skills in this Data Engineering project! In this course you will apply a variety of data engineering skills and techniques you have learned as part of the previous courses in the IBM Data Engineering Professional Certificate. You will demonstrate your knowledge of Data Engineering by assuming the role of a Junior Data Engineer who has recently joined an organization and be presented with a real-world use case that requires architecting and implementing a data analytics platform. |
|
Data Engineering Career Guide and Interview Preparation (Coursera) https://www.coursera.org/learn/data-engineering-career-guide-and-interview-preparation This course is designed to prepare you to enter the job market as a data engineer. It provides guidance about the regular functions and tasks of data engineers and their place in the data ecosystem, as well as the opportunities of the profession and some options for career development. It explains practical techniques for creating essential job-seeking materials such as a resume and a portfolio, as well as auxiliary tools like a cover letter and an elevator pitch. You will learn how to find and |
|
Data Engineering with MS Azure Synapse Apache Spark Pools (Coursera) https://www.coursera.org/learn/data-engineering-with-ms-azure-synapse-apache-spark-pools In this course, you will learn how to perform data engineering with Azure Synapse Apache Spark Pools, which enable you to boost the performance of big-data analytic applications by in-memory cluster computing. You will learn how to differentiate between Apache Spark, Azure Databricks, HDInsight, and SQL Pools and understand the use-cases of data-engineering with Apache Spark in Azure Synapse Analytics. You will also learn how to ingest data using Apache Spark Notebooks in Azure Synapse Analytic |
|
Data for Machine Learning (Coursera) https://www.coursera.org/learn/data-machine-learning This course is all about data and how it is critical to the success of your applied machine learning model. Completing this course will give learners the skills to: Understand the critical elements of data in the learning, training and operation phases Understand biases and sources of data Implement techniques to improve the generality of your model Explain the consequences of overfitting and identify mitigation measures Implement appropriate test and validation measures. Demonstrate how the acc |
|
Data Integration with Microsoft Azure Data Factory (Coursera) https://www.coursera.org/learn/azure-data-factory-data-integration In this course, you will learn how to create and manage data pipelines in the cloud using Azure Data Factory. This course is part of a Specialization intended for Data engineers and developers who want to demonstrate their expertise in designing and implementing data solutions that use Microsoft Azure data services. It is ideal for anyone interested in preparing for the DP-203: Data Engineering on Microsoft Azure exam (beta). This is the third course in a program of 10 courses to help prepare |
|
Data Literacy – What is it and why does it matter? (Coursera) https://www.coursera.org/learn/data-literacy-what-is-it-and-why-does-it-matter You might already know that data is not neutral. Our values and assumptions are influenced by the data surrounding us - the data we create, the data we collect, and the data we share with each other. Economic needs, social structures, or algorithmic biases can have profound consequences for the way we collect and use data. Most often, the result is an increase of inequity in the world. Data also changes the way we interact. It shapes our thoughts, our feelings, our preferences and actions. It de |
|
Data Management and Visualization (Coursera) https://www.coursera.org/learn/data-visualization Whether being used to customize advertising to millions of website visitors or streamline inventory ordering at a small restaurant, data is becoming more integral to success. Too often, we’re not sure how use data to find answers to the questions that will make us more successful in what we do. In this course, you will discover what data is and think about what questions you have that can be answered by the data – even if you’ve never thought about data before. Based on existing data, you will l |
|
Data Management for Clinical Research (Coursera) https://www.coursera.org/learn/clinical-data-management This course presents critical concepts and practical methods to support planning, collection, storage, and dissemination of data in clinical research. Understanding and implementing solid data management principles is critical for any scientific domain. Regardless of your current (or anticipated) role in the research enterprise, a strong working knowledge and skill set in data management principles and practice will increase your productivity and improve your science. Our goal is to use these m |
|
Data Manipulation at Scale: Systems and Algorithms (Coursera) https://www.coursera.org/learn/data-manipulation Data analysis has replaced data acquisition as the bottleneck to evidence-based decision making --- we are drowning in it. Extracting knowledge from large, heterogeneous, and noisy datasets requires not only powerful computing resources, but the programming abstractions to use them effectively. The abstractions that emerged in the last decade blend ideas from parallel databases, distributed systems, and programming languages to create a new class of scalable data analytics platforms that form |
|
Data Manipulation in JavaScript (Coursera) https://www.coursera.org/learn/javascript-data-manipulation This course builds on the skills from the previous course and goes further into managing and manipulating data with JavaScript. You will learn methods for validating and handling data provided by users or coming from an external data source. This course includes a challenge in the form of a seat reservation system, as well as a project that pulls data in from an external data source. The course objectives include validation basics in JavaScript and jQuery; jQuery form validation plugin features |
|
Data Manipulation in RPA (Coursera) https://www.coursera.org/learn/data-manipulation-in-rpa The Data Manipulation in RPA course will provide knowledge about Variables, Arguments, and Data Manipulation. It will also introduce you to Variables and Arguments, their types, and their application in automation projects. In the later part of the course, you will learn about data manipulation in Studio. You will also learn about the different methods and operations performed on different data types and their usage in automation projects. Building on each concept, there will be demonstration |
|
Data Mining Methods (Coursera) https://www.coursera.org/learn/data-mining-methods This course covers the core techniques used in data mining, including frequent pattern analysis, classification, clustering, outlier analysis, as well as mining complex data and research frontiers in the data mining field. 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. These fully accredited graduate degrees offer targeted courses, short 8-week sessions, and pay-as-you-go tuition. Admis |
|
Data mining of Clinical Databases - CDSS 1 (Coursera) https://www.coursera.org/learn/cdss1 This course will introduce MIMIC-III, which is the largest publicly Electronic Health Record (EHR) database available to benchmark machine learning algorithms. In particular, you will learn about the design of this relational database, what tools are available to query, extract and visualise descriptive analytics. The schema and International Classification of Diseases coding is important to understand how to map research questions to data and how to extract key clinical outcomes in order to d |
|
Data Mining Pipeline (Coursera) https://www.coursera.org/learn/data-mining-pipeline This course introduces the key steps involved in the data mining pipeline, including data understanding, data preprocessing, data warehousing, data modeling, interpretation and evaluation, and real-world 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. These fully accredited graduate degrees offer targeted courses, short 8-week sessions, and pay-as-you-go tuition. Admission i |
|
Data Mining Project (Coursera) https://www.coursera.org/learn/data-mining-project Note: You should complete all the other courses in this Specialization before beginning this course. This six-week long Project course of the Data Mining Specialization will allow you to apply the learned algorithms and techniques for data mining from the previous courses in the Specialization, including Pattern Discovery, Clustering, Text Retrieval, Text Mining, and Visualization, to solve interesting real-world data mining challenges. Specifically, you will work on a restaurant review data se |
|
Data Modeling in Power BI (Coursera) https://www.coursera.org/learn/data-modeling-in-power-bi This course forms part of the Microsoft Power BI Analyst Professional Certificate. This Professional Certificate consists of a series of courses that offers a good starting point for a career in data analysis using Microsoft Power BI. In this course, you'll learn how to use Power BI to create and maintain relationships in a data model and form a model using multiple Schemas. You'll explore the basics of DAX, Power BI's expression language, and add calculations to your model to create elements a |
|
Data Pipelines with TensorFlow Data Services (Coursera) https://www.coursera.org/learn/data-pipelines-tensorflow Bringing a machine learning model into the real world involves a lot more than just modeling. This Specialization will teach you how to navigate various deployment scenarios and use data more effectively to train your model. In this third course, you will: - Perform streamlined ETL tasks using TensorFlow Data Services - Load different datasets and custom feature vectors using TensorFlow Hub and TensorFlow Data Services APIs - Create and use pre-built pipelines for generating highly reproducible |
|
Data Privacy Fundamentals (Coursera) https://www.coursera.org/learn/northeastern-data-privacy This course is designed to introduce data privacy to a wide audience and help each participant see how data privacy has evolved as a compelling concern to public and private organizations as well as individuals. In this course, you will hear from legal and technical experts and practitioners who encounter data privacy issues daily. This course will review theories of data privacy as well as data privacy in the context of social media and artificial intelligence. It will also explore data privacy |
|
Data Processing and Feature Engineering with MATLAB (Coursera) https://www.coursera.org/learn/feature-engineering-matlab In this course, you will build on the skills learned in Exploratory Data Analysis with MATLAB to lay the foundation required for predictive modeling. This intermediate-level course is useful to anyone who needs to combine data from multiple sources or times and has an interest in modeling. These skills are valuable for those who have domain knowledge and some exposure to computational tools, but no programming background. To be successful in this course, you should have some background in ba |
|
Data Processing Using Python (Coursera) https://www.coursera.org/learn/python-data-processing This course (The English copy of "用Python玩转数据" |
|
Data Science at Scale - Capstone Project (Coursera) https://www.coursera.org/learn/datasci-capstone In the capstone, students will engage on a real world project requiring them to apply skills from the entire data science pipeline: preparing, organizing, and transforming data, constructing a model, and evaluating results. Through a collaboration with Coursolve, each Capstone project is associated with partner stakeholders who have a vested interest in your results and are eager to deploy them in practice. These projects will not be straightforward and the outcome is not prescribed -- you w |
|
Data Science Ethics (Coursera) https://www.coursera.org/learn/data-science-ethics What are the ethical considerations regarding the privacy and control of consumer information and big data, especially in the aftermath of recent large-scale data breaches? This course provides a framework to analyze these concerns as you examine the ethical and privacy implications of collecting and managing big data. Explore the broader impact of the data science field on modern society and the principles of fairness, accountability and transparency as you gain a deeper understanding of the i |
|
Data Science for Business Innovation (Coursera) https://www.coursera.org/learn/data-science-for-business-innovation This is your chance to learn all about Data Science for Business innovation and future-proof your career. Match your business experience tech and analytics! The Data Science for Business Innovation nano-course is a compendium of the must-have expertise in data science for executives and managers to foster data-driven innovation. The course explains what Data Science is and why it is so hyped. You will learn: * the value that Data Science can create * the main classes of problems that Data Sci |