A database is used to store and retrieve structured, semi-structured or raw data or information, s

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Do not deal with the manual with terms of reference statements and basic documents that cannot be obtained in order to avoid the MongoDB problem. Please include the connection to one of the MongoDB données base, comment on simple CRUD operations and sujets clés que l'agrégation, l'indexation, la mode des données et les Transaction. 1- Install MongoDB 2- Implement MongoDB 3- Use of documents and collectibles 4 - Leadership Committee 5- Execute CRUD commands (create, read, update, delete) avec mongo shell 6- Type the register in a MongoDB database 7- Reset the base to remonter specific documents depuis mongo shell. 8- Lagrégation 9- Indexing 10- Amending institutions and transactions

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Learn how to create impactful marketing campaigns by combining data insights with effective communication strategies. This class will teach you to analyze customer data, identify trends, and design campaigns that resonate with your audience while delivering measurable results. Perfect for anyone looking to elevate their marketing efforts.

In this course you will learn how to transform your data into useful information for decision making through visualizations. You will also create your data model. Cake Graphics. Bar Charts. Dispersion. Measurements. DAX expressions. At the end of the course you will have created your first report in Power BI Desktop.

Introduction to Databases Learn about the importance of databases in the digital world, their role in managing and exploiting data, and the fundamental concepts of structured storage. SQL for Beginners Learn the basics of SQL: SELECT, INSERT, UPDATE, DELETE queries, joins, aggregate functions and more to effectively interact with a database. MySQL and WAMP Server Install and configure WAMP Server to create and manage MySQL databases locally. Learn how to use phpMyAdmin for easy management. DBever and SQL Server Introduction to professional database management tools: Get started with DBever and SQL Server to administer, analyze and optimize your databases. Database Management and Operation Learn best practices for database management: indexing, query optimization, data security and backup. Database Administration Understand the roles of a database administrator (DBA): user management, access rights, maintenance and performance monitoring. Practical DBMS Project Apply your knowledge to a real-world database management project, from design to deployment, optimization and administration.

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This class covers statistics and statistical methods for data analysis which cuts across all industry and disciplines. Sample topics, Statistical calculations Statistical methods Statistical analysis Quantitative analysis Quantitative analysis techniques Non Quantitative data analysis Research methods Research methods paper section Mathematical analysis Statistical software and spreadsheets like Rsutdio, Excel, SPSS, and many others. and any statistical topic requests by students

The Topics: 1. Winning Proposal Writing 2. Research Projects writing with implementable Deliverable & 3. Practical workshop using SPSS Area to be covered: 1. Concept Paper 2. Topic Development 3. Winning Proposal Development 4. Questionnaires Design 5. Data Collection Method’s & Tools 6. Data Analysis Tools & visualization 7. Project Integration 8. Storytellingand report making 9. Project/ Proposal Presentation Techniques 10. Plagiarism Management 11. Journal publication

I am a Ph.D. student at the University of Luxembourg. For the past 4 years, I taught the University: statistics and probability theory to first-year students, and economics to 3th-year students. I really enjoy teaching. I am looking forward to helping students when they need reinforcement on different subjects, or anyone interested in learning the following topics: For maths: System of equations, derivatives, integrals, type of equations, etc. For statistics: Probability theory, descriptive statistics, regression analysis, multivariate analysis, hypothesis testing, and methods for causal inference. For young professionals: I have extensive experience in data analysis, data management, and statistical modeling. My class mixes both theoretical and practical parts using financial data as examples. If you are interested, just write me a message telling me what topics are you interested in learning.

Dive into the exciting world of bioinformatics, where biology meets data science! This class equips you with essential bioinformatics and data analysis skills to explore and analyze biological data effectively. You will learn how to manage, visualize, and interpret complex datasets using tools like R or Python, understand sequence alignment and annotation techniques, and delve into topics like genomics, transcriptomics, and proteomics. What You'll Learn: Data Handling: Fundamentals of working with large biological datasets, including cleaning, formatting, and preprocessing data. Programming Skills: Basics of R or Python for bioinformatics applications, including scripting and automating analyses. Genomic Analysis: Sequence alignment, gene annotation, and exploring genomic databases. Statistical Analysis: Applying statistical techniques to identify patterns and draw meaningful conclusions. Visualization: Creating clear and informative plots for biological data. Applications: Perform differential gene expression analysis to understand disease mechanisms. Analyze genetic variants to study evolutionary patterns or predict disease risks. Explore protein structures and functions for drug discovery. Use bioinformatics pipelines to support cutting-edge research in academia or industry. Whether you're aspiring to work in biotech, academia, or data science, this class provides the foundation you need to bridge biology and technology, opening doors to a range of exciting opportunities.

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In this class you will learn the basic, intermediate and advance topics of database development. How to analyze the requirements, design the basic structure of database and then implementing and then to retrieve the data. The basic concepts regarding the normalization will also be discussed.