Database Systems: All Concepts of Graduate Level for CS Graduates

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I offer personalized courses that cover a wide range of topics, from the basics of relational database management to advanced data manipulation using query languages such as SQL and tools such as DBSM, MySQL, and PostgreSQL. My courses are tailored to the needs and learning styles of each student, and I am committed to helping my students achieve their individual learning goals. Whether you are a beginner or looking to improve your skills, I can help you develop your relational database management skills and take your expertise in this field to the next level. I am excited to guide you through the world of relational database management and help you master the skills necessary to succeed in this field. Please do not hesitate to contact me for more information about my services and how I can help you achieve your relational database management goals.

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Module 1: SQL Overview Outlining SQL as the cornerstone of database activity Applying the ANSI/ISO standards Describing the fundamental building blocks: tables, columns, primary keys, and foreign keys Module 2: Building the Database Schema - Creating tables and columns Building tables with CREATE TABLE Modifying table structure with ALTER TABLE Adding columns to an existing table Removing tables with DROP TABLE - Protecting data integrity with constraints Guaranteeing uniqueness with primary key constraints Enforcing integrity with foreign key constraints Imposing business rules with check constraints - Improving performance with indexes Expediting data retrieval with indexes Recommending guidelines for index creation Module 3: Manipulating Data - Modifying table contents Adding table rows with INSERT Changing row content with UPDATE Removing rows with DELETE - Applying transactions Controlling transactions with COMMIT and ROLLBACK Deploying BEGIN TRANSACTION in SQL Server Module 4: Working with the SELECT Statement - Writing Single Table queries Retrieving data with SELECT Specifying column expressions Sorting the result with ORDER BY Handling NULL values in expressions - Restricting rows with the WHERE filter Testing for equality or inequality Applying wildcard characters Avoiding NULL value pitfalls Module 5: Querying Multiple Tables - Applying the ANSI/ISO standard join syntax Matching related rows with INNER JOIN Including nonmatched rows with OUTER JOIN Creating a Cartesian product with CROSS JOIN - Combining results with set operators Stacking results with UNION Identifying matching rows with INTERSECT Utilizing EXCEPT to find nonmatching rows Module 6: Employing Functions in Data Retrieval - Processing data with row functions Conditional formatting with the CASE expression Utilizing the CASE expression to simulate IF tests Dealing with NULL values - Performing analysis with aggregate functions Summarizing data using SUM, AVG and COUNT Finding the highest/lowest values with MAX and MIN Defining the summary level with GROUP BY Applying filter conditions with HAVING Module 7: Constructing Nested Queries - Applying subqueries in filter conditions Creating correlated vs. noncorrelated subqueries Testing the existence of rows - Including subqueries in expressions Placing subqueries in the column list Creating complex expressions containing subqueries Handling subqueries that return no rows Module 8: Developing In-Line and Stored Views - Breaking down complex problems Selecting data from a query result set Using subqueries in the FROM clause - Creating views in a database Building reusable code Creating updateable vs. non-updateable views

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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.