Design course and management of relational databases

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From 10.34 £ /h

I propose a simplified relational database course for beginners. The goal is to learn how to do data design and main SQL queries for database management, table creation and deletion.

Location

Online from Morocco

Age

Children (7-12 years old)

Teenagers (13-17 years old)

Adults (18-64 years old)

Seniors (65+ years old)

Student level

Beginner

Duration

60 minutes

120 minutes

The class is taught in

French

Arabic

English

Skills

Database

Availability of a typical week

(GMT -05:00)

New York

Online via webcam

Mon

Tue

Wed

Thu

Fri

Sat

Sun

00-04

04-08

08-12

12-16

16-20

20-24

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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.

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Performance Optimization: Speed up slow applications (database queries, API responses, bundle size)
CI/CD Setup: Automate your deployment pipeline (GitHub Actions, testing, monitoring)

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❌ "Payment integration (Stripe) not working"

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Frontend: React, Next.js, TypeScript, Vue, Angular
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Databases: PostgreSQL, MySQL, MongoDB, Redis
Cloud: AWS (EC2, RDS, S3), Vercel, Netlify, Render
DevOps: Docker, CI/CD, GitHub Actions, Nginx

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Students: Fix your project before the deadline
Junior Developers: Debug production issues you can't solve alone
Freelancers: Get unstuck on client projects fast
Startups: Fix and deploy your MVP without hiring a full-time engineer

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Live Debugging Session: We fix it together via screen share
Code Review: I show you how to prevent the issue in the future
Documentation: You get a summary of what was fixed and why

Average Resolution Time:

Simple bugs: 1-2 hours
Deployment issues: 2-3 hours
Complex debugging: 3-5 hours

Urgent projects accepted (same-day availability for emergencies).

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Introduction to Python and environment setup
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Operators and expressions
Conditional statements
Types of loops and loop control
Functions and scope
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Generators, yield, and closures
Decorators
Object-Oriented Programming (classes, inheritance, polymorphism, encapsulation)
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Using Pandas DataFrames and Series
Data cleaning, filtering, and transformation
Handling missing values and duplicates
Grouping, aggregation, and pivot tables
Exporting data to CSV and Excel
Real-world exercises with sample datasets