✨Project: Applying all learned techniques to a comprehensive project - Preparing Data for Analysis - Developing and Evaluating Models - Presenting Insights and Solutions.
01
Introduction to database
02
Data Modeling
03
Types of databases
04
ERD
05
How to choose the best database for your data
06
SQL vs NoSQL database
07
SQL for data analysis
08
Mapping
01
Work with Excel Sheets
02
Create graphs using Excel
03
Writing Excel formulas
04
Create Excel dashboards
✨Project: End-to-End Data Projects - Report Generation - Story Telling
01
Introduction to data analysis tools
02
Power BI vs Tableau
03
Create Power BI dashboard
04
Integrate Power BI with different data sources
05
Introduction to Data Engineering
01
Introduction to power query
02
Preprocessing data
03
Why using power query
04
Apply data transformations
05
Power query interface
06
Introduction to M language
07
Supported data sources
08
Best practices
09
Cleaning data
01
What is a Data Warehouse?
02
General Cloud Concepts : IaaS, PaaS, SaaS
03
ETL (Extract, Transform, Load)
04
Main Cloud Providers: AWS, Azure, Google Cloud (GCP)
05
ELT (Extract, Load, Transform)
06
Data Lake vs Data Warehouse vs Data Marts
01
Apply your full data analysis pipeline from data collection, cleaning, exploration, and visualization to generating actionable insights on a real-world dataset.
01
أكثر من 6 مشاريع.
02
استخلاص رؤى من جميع أنواع البيانات. Conclude Insights from all kinds of Data
03
إجراء جميع عمليات المعالجة المسبقة للبيانات اللازمة لأي مشكلة. Perform all Data preprocessing required for a problem.
04
إنشاء مجموعات بيانات بناءً على المشكلة. وقواعد البيانات. Generate Datasets based on the problem
05
اختيار المنهجية الأنسب لحل أي مشكلة تحسين. Choose the best methodology to solve any optimization problem
06
إتقان الأدوات الرئيسية لعلم البيانات. Mastering main tools of Data Science
07
ضبط النماذج وتخصيص هياكلها. Fine tune models and customize architectures
08
مقابلات تجريبية + تدريب مهني (Mock Interviews + Career Coaching)