DATA SCIENCE/ML/AI GENERAL

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Useful links

Relational Database https://www.freecodecamp.org/learn/relational-database/
Scientific Computing with Python https://www.freecodecamp.org/learn/scientific-computing-with-python/
Data Analysis with Python https://www.freecodecamp.org/learn/data-analysis-with-python/
Machine Learning with Python https://www.freecodecamp.org/learn/machine-learning-with-python/

All the courses mentioned above are free including certification. They are relatively easy projects and you don't need to see all the classes, you can jump straight to the project and claim your certificate.

Learn Data Science 6h - FreeCodeCamp https://www.youtube.com/watch?v=ua-CiDNNj30
Learn Data Science in 10 Hours - Edureka https://www.youtube.com/watch?v=-ETQ97mXXF0

The videos above work as a summary on Data Science for those who have not had contact. I highly recommend it, you can enable translated subtitles as well if you don't speak English.

Roadmap

1. Programming

Data Types, Variables, and Operators
Control Flow and Loops
Functions and Modules
Object-Oriented Programming
Exception Handling

2. Database Management

Relational Database Management Systems (RDBMS)
SQL Fundamentals
NoSQL Databases
Data Warehousing

3. Data Modeling

Conceptual, Logical, and Physical Data Modeling
Entity-Relationship Diagrams (ERD)
Normalization

4. Data Integration

Extract, Transform, and Load (ETL) Process
Data Integration Tools
Data Migration

5. Data Processing

Data Pipelines
Batch Processing
Stream Processing
Apache Spark

6. Cloud Computing

Cloud Platforms
Cloud Data Warehouses
Cloud Data Lakes
Cloud Services (AWS, Azure, GCP)

7. Data Governance

Data Quality
Data Security
Data Privacy
Compliance and Regulations

8. Big Data

Hadoop Ecosystem
MapReduce
Apache Hive
Apache Pig

9. Data Visualization

Data Visualization Tools
Dashboarding Tools
Business Intelligence (BI) Tools

10. Machine Learning

Machine Learning Fundamentals
Feature Engineering
Model Training
Model Deployment

Projects for portfolio

Building a Data Pipeline: Develop an end-to-end data pipeline that extracts data from a source, transforms it, and loads it into a destination. Use tools like Apache Kafka, Apache Spark, and AWS S3 to build the pipeline
Building a Data Warehouse: Design and build a data warehouse from scratch. Use tools like Snowflake, AWS Redshift, or Google BigQuery to create the data warehouse. Load data from different sources and build a reporting dashboard to visualize the data
Building a Real-time Streaming System: Build a real-time streaming system that processes data as it arrives. Use tools like Apache Kafka, Apache Flink, and Apache NiFi to build the system. Use the system to process data from a source and visualize the data in real-time

Good sources for large data sets to practice with

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