Coursera Courses |
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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 |
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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 |
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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 |
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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 |
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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 |
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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 |
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Data Mining Project (Coursera) https://www.coursera.org/learn/data-mining-theory-practice-project Data Mining Project offers step-by-step guidance and hands-on experience of designing and implementing a real-world data mining project, including problem formulation, literature survey, proposed work, evaluation, discussion and future work. 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-yo |
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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 |
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Data Modeling, Transformation, and Serving (Coursera) https://www.coursera.org/learn/data-modeling-transformation-serving In this course, you’ll model, transform, and serve data for both analytics and machine learning use cases. You’ll explore various data modeling techniques for batch analytics, including normalization, star schema, data vault, and one big table, and you’ll use dbt to transform a dataset based on a star schema and one big table. You’ll also compare the Inmon vs Kimball data modeling approaches for data warehouses. You’ll model and transform a tabular dataset for machine learning purposes. You’ll a |
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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 |
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Data Privacy and Protection Standards (Coursera) https://www.coursera.org/learn/data-privacy-and-protection-standards In today's digital age, Data Privacy and Protection Standards are pivotal for organizations across all sectors to safeguard sensitive information, comply with international regulations, and maintain the trust of clients and customers. This course provides a comprehensive understanding of the foundational principles of data privacy, the latest in protection standards, and practical approaches to implementing robust data protection measures. Participants will explore key regulations such as the GD |
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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 |
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Data Privacy, Security, Governance, Risk and Compliance (Coursera) https://www.coursera.org/learn/data-privacy-security-governance-risk-and-compliance Whether you’re an aspiring data engineer, data architect, business analyst, or data scientist, a strong foundation in data security is crucial for any data management professional. By gaining practical experience and comprehensive knowledge, you will strengthen your resume and unlock exciting career opportunities in the dynamic field of data security and protection. This course provides insight into data privacy, security, and governance. You will learn to implement effective strategies for p |
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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 |
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Data Processing and Optimization with Generative AI (Coursera) https://www.coursera.org/learn/data-processing-and-optimization-with-generative-ai This course focuses on advanced methods for data cleaning, preparation, and optimization using AI-assisted tools. You'll learn to generate synthetic data, address privacy concerns and data limitations in your projects. Discover how to leverage AI to identify and resolve complex data quality issues, ensuring your datasets are primed for analysis. Upon completion of this course, you'll be able to: Generate synthetic data using generative AI models Implement advanced data cleaning techniques wi |
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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" |
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Data Processing with Azure (Coursera) https://www.coursera.org/learn/data-processing-with-azure This Azure training course is designed to equip students with the knowledge need to process, store and analyze data for making informed business decisions. Through this Azure course, the student will understand what big data is along with the importance of big data analytics, which will improve the students mathematical and programming skills. Students will learn the most effective method of using essential analytical tools such as Python, R, and Apache Spark. |
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Data Science as a Field (Coursera) https://www.coursera.org/learn/data-science-as-a-field This course provides a general introduction to the field of Data Science. It has been designed for aspiring data scientists, content experts who work with data scientists, or anyone interested in learning about what Data Science is and what it’s used for. Weekly topics include an overview of the skills needed to be a data scientist; the process and pitfalls involved in data science; and the practice of data science in the professional and academic world. This course is part of CU Boulder’s Maste |
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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 |
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Data Science Capstone (Coursera) https://www.coursera.org/learn/data-science-project The capstone project class will allow students to create a usable/public data product that can be used to show your skills to potential employers. Projects will be drawn from real-world problems and will be conducted with industry, government, and academic partners. |
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Data Science Companion (Coursera) https://www.coursera.org/learn/data-science-companion-matlab The Data Science Companion provides an introduction to data science. You will gain a quick background in data science and core machine learning concepts, such as regression and classification. You’ll be introduced to the practical knowledge of data processing and visualization using low-code solutions, as well as an overview of the ways to integrate multiple tools effectively to solve data science problems. You will then leverage cloud resources from Amazon Web Services to scale data processing |
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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 |
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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 |
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Data Science for Professionals (Coursera) https://www.coursera.org/learn/data-science-for-professionals Data science has become indispensable across industries, driving informed decision-making and uncovering valuable insights from data. This course is designed for professionals seeking to leverage data science techniques and tools to extract meaningful information from data and drive organizational success. From data wrangling to predictive modeling, this course covers key concepts and practical skills essential for professionals in today's data-driven world. This course is designed for Busines |
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Data Science Fundamentals for Data Analysts (Coursera) https://www.coursera.org/learn/data-science-fundamentals-for-data-analysts In this course we're going to guide you through the fundamental building blocks of data science, one of the fastest-growing fields in the world! With the help of our industry-leading data scientists, we’ve designed this course to build ready-to-apply data science skills in just 15 hours of learning. First, we’ll give you a quick introduction to data science - what it is and how it is used to solve real-world problems. For the rest of the course, we'll teach you the skills you need to apply fou |
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Data Science in Health Technology Assessment (Coursera) https://www.coursera.org/learn/health-economics-and-hta This course explores key concepts and methods in Health Economics and Health Technology Assessment (HTA) and is intended for learners who have a foundation in data science, clinical science, regulatory and are new to this field and would like to understand basic principles used by payers for their reimbursement decisions. |
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Data Science in Real Life (Coursera) https://www.coursera.org/learn/real-life-data-science Have you ever had the perfect data science experience? The data pull went perfectly. There were no merging errors or missing data. Hypotheses were clearly defined prior to analyses. Randomization was performed for the treatment of interest. The analytic plan was outlined prior to analysis and followed exactly. The conclusions were clear and actionable decisions were obvious. Has that every happened to you? Of course not. Data analysis in real life is messy. How does one manage a team facing real |
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Data Science in Stratified Healthcare and Precision Medicine (Coursera) https://www.coursera.org/learn/datascimed An increasing volume of data is becoming available in biomedicine and healthcare, from genomic data, to electronic patient records and data collected by wearable devices. Recent advances in data science are transforming the life sciences, leading to precision medicine and stratified healthcare. In this course, you will learn about some of the different types of data and computational methods involved in stratified healthcare and precision medicine. You will have a hands-on experience of worki |
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Data Science Math Skills (Coursera) https://www.coursera.org/learn/datasciencemathskills Data science courses contain math—no avoiding that! This course is designed to teach learners the basic math you will need in order to be successful in almost any data science math course and was created for learners who have basic math skills but may not have taken algebra or pre-calculus. Data Science Math Skills introduces the core math that data science is built upon, with no extra complexity, introducing unfamiliar ideas and math symbols one-at-a-time. Learners who complete this course wi |
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Data Science Methodology (Coursera) https://www.coursera.org/learn/data-science-methodology If there is a shortcut to becoming a Data Scientist, then learning to think and work like a successful Data Scientist is it. In this course, you will learn and then apply this methodology that you can use to tackle any Data Science scenario. You’ll explore two notable data science methodologies, Foundational Data Science Methodology, and the six-stage CRISP-DM data science methodology, and learn how to apply these data science methodologies. Most established data scientists follow these or simil |
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Data Science Project: MATLAB for the Real World (Coursera) https://www.coursera.org/learn/matlab-capstone Like most subjects, practice makes perfect in Data Science. In the capstone project, you will apply the skills learned across courses in the Practical Data Science with MATLAB specialization to explore, process, analyze, and model data. You will choose your own pathway to answer key questions with the provided data. To complete the project, you must have mastery of the skills covered in other courses in the specialization. The project will test your ability to import and explore your data, |
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Data Science with NumPy, Sets, and Dictionaries (Coursera) https://www.coursera.org/learn/numpy-data-science Become proficient in NumPy, a fundamental Python package crucial for careers in data science. This comprehensive course is tailored to novice programmers aspiring to become data scientists, software developers, data analysts, machine learning engineers, data engineers, or database administrators. Starting with foundational computer science concepts, such as object-oriented programming and data organization using sets and dictionaries, you'll progress to more intricate data structures like array |
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Data Science with R - Capstone Project (Coursera) https://www.coursera.org/learn/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 |
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Data Sciences in Pharma - Patient Centered Outcomes Research (Coursera) https://www.coursera.org/learn/data-science-patient-centered-research-in-pharma-industry The course is targeted toward people who are interested in how patient experience data and clinical outcome assessment (COA) data can be used as evidence across drug development, in the pharmaceutical industry. By the end of the course you will better understand how this data is collected and analysed to evidence how patients feel, function or survive in the context of a clinical trial. More specifically, the course will cover: i) a background to COAs; ii) a background to patient experience data |
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Data Scientist Career Guide and Interview Preparation (Coursera) https://www.coursera.org/learn/career-guide-and-interview-prep-for-data-science-pc Data science 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 scientist 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 a |
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https://www.coursera.org/learn/data-security If you are an associate-level cybersecurity analyst who is working in security operation centers, this course will help you explore data type categories in context to network security analytics. By the end of the course, you will be able to: • Explain the data that is available to the network security analysis •Describe the various types of data used in monitoring network security • Describe the deployment and use of SIEMs to collect, sort, process, prioritize, store, and report alarms • De |
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Data Storage and Queries (Coursera) https://www.coursera.org/learn/data-storage-and-queries In this course, you will learn about the raw ingredients and processes that are used to physically store data on disk and in memory. You’ll explore different storage systems, including object, block, and file storage, as well as databases, that are built on top of these raw ingredients. You’ll also get a chance to use the Cypher language to query a Neo4j graph database, and perform vector similarity search, a key feature behind generative AI and large language models. You will explore the evolut |
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Data Storage in Microsoft Azure (Coursera) https://www.coursera.org/learn/data-storage-microsoft-azure Azure provides a variety of ways to store data: unstructured, archival, relational, and more. In this course, you will learn the basics of storage management in Azure, how to create a Storage Account, and how to choose the right model for the data you want to store in the cloud. This course 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 anyone interest |
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Data Storage in Microsoft Azure for Associate Developers (Coursera) https://www.coursera.org/learn/data-storage-microsoft-azure-developers Azure provides a variety of ways to store data: unstructured, archival, relational, and more. In this course, you will learn the basics of storage management in Azure, how to create a Storage Account, and how to choose the right model for the data you want to store in the cloud. This course 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 anyone interest |
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https://www.coursera.org/learn/data-storytelling-fractal In today's data-driven world, the ability to transform complex information into compelling narratives is essential. This course equips you with the principles and techniques of storytelling, coupled with data visualization skills, to craft captivating stories that engage and influence diverse audiences. Through hands-on exercises and real-world case studies, you will learn to distill intricate data into clear and concise narratives, enabling you to drive organizational impact and make informed |
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Data Storytelling with Power BI (Coursera) https://www.coursera.org/learn/data-storytelling-with-power-bi Welcome to the Data Storytelling with Power BI course, where you'll embark on a journey to acquire practical expertise in data transformation and visualization. Leverage the potential of Power BI to craft narratives through structured data, leading to the discovery of more profound insights. Throughout this course, you'll explore the industry-specific applications of Power BI and delve into its various features and functionalities. By the end of this course, you’ll be able to: • Explain the di |
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Data Structures & Backend with Java (Coursera) https://www.coursera.org/learn/data-structures--backend-with-java This comprehensive course delves deep into the nuances of data structures and backend development with Java. The curriculum is strategically designed across three core modules, seamlessly bridging the understanding of theory with practical application. In the first module, we delve into Java-based data structures, focusing on arrays, multi-dimensional arrays, the String class, and the Java Collections Framework. You'll gain a foundational understanding of efficient data storage and manipulation |
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Data Structures and Algorithms (Coursera) https://www.coursera.org/learn/developer-data-structures-and-algorithms This is the third course in the Amazon Junior Software Developer Professional Certificate. In this course, you will gain a deep understanding of various fundamental data structures and algorithms essential for building efficient and scalable software solutions. Starting with Advanced Data Structures, you'll explore arrays, ArrayLists, linked lists, stacks, queues, and maps, understanding their implementations, operations, advantages, and use cases. Moving on to Searching and Sorting Algorithms, |
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Data Structures and Algorithms (I) (Coursera) https://www.coursera.org/learn/data-structures-algorithms-1 By learning this course, you will get a comprehensive grasp of vector and list and the ability to use them in solving real problems. By the end of this course, you will be able to evaluate data structures and algorithms in terms of asymptotic complexity, analyze storage/time complexity of iterative/recursive algorithms, implement vector and list, understand/implement basic sorting algorithms such as Bubblesort, Insertionsort, and Selectionsort, understand/implement search algorithms such as |
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Data Structures and Design Patterns for Game Developers (Coursera) https://www.coursera.org/learn/data-structures-design-patterns This course is a stand-alone course that builds on the knowledge included in the C# Programming for Unity Game Development Specialization, so the course assumes you have the prerequisite knowledge from that Specialization. You should make sure you have that knowledge, either by taking those courses or from personal experience, before tackling this course. Throughout this course you'll build on your foundational C# and Unity knowledge by developing more robust games with better object-oriented de |
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Data Structures and Performance (Coursera) https://www.coursera.org/learn/data-structures-optimizing-performance How do Java programs deal with vast quantities of data? Many of the data structures and algorithms that work with introductory toy examples break when applications process real, large data sets. Efficiency is critical, but how do we achieve it, and how do we even measure it? This is an intermediate Java course. We recommend this course to learners who have previous experience in software development or a background in computer science, and in particular, we recommend that you have taken the fi |
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Data Structures in C (Coursera) https://www.coursera.org/learn/data-structures-in-c Covering dynamic memory allocation for optimizing memory utilization, Data Structures in C explores ways to handle multiple variables collectively. In this course, you’ll delve into the central concept of pointers for managing the storage and retrieval of memory. Explore and understand structures, a C-specific user-defined data type combining assorted data items. |
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Data Transformation in the Cloud (Coursera) https://www.coursera.org/learn/data-transformation-in-the-cloud Hi learner! This is the third course of the Google Cloud Data Analytics Certificate. Tap into your creativity as you explore the world of advanced principles of data visualization. You'll discover the benefits and challenges of transforming data in the cloud and the common tools and methods used to collect, process, and store data. |
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Data Visualization and Communication with Tableau (Coursera) https://www.coursera.org/learn/analytics-tableau One of the skills that characterizes great business data analysts is the ability to communicate practical implications of quantitative analyses to any kind of audience member. Even the most sophisticated statistical analyses are not useful to a business if they do not lead to actionable advice, or if the answers to those business questions are not conveyed in a way that non-technical people can understand. In this course you will learn how to become a master at communicating business-relevan |
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Data Visualization and Dashboards with Excel and Cognos (Coursera) https://www.coursera.org/learn/data-visualization-dashboards-excel-cognos Learn how to create data visualizations and dashboards using spreadsheets and analytics tools. This course covers some of the first steps for telling a compelling story with your data using various types of charts and graphs. You'll learn the basics of visualizing data with Excel and IBM Cognos Analytics without having to write any code. You'll start by creating simple charts in Excel such as line, pie and bar charts. You will then create more advanced visualizations with Treemaps, Scatter Cha |