7 Baby steps to start with Machine Learning:

1. Start with Python
2. Learn to use Google Colab
3. Take a Pandas tutorial
4. Then a Seaborn tutorial
5. Decision Trees are a good first algorithm
6. Finish Kaggle's "Intro to Machine Learning"
7. Solve the Titanic challenge

Data Science Roadmap

Career Path for a Data Analyst

Education: Start by earning a bachelor's degree in fields like math, stats, economics, or computer science.

Skills Growth: Learn programming (Python/R), data tools (SQL/Excel), and visualization. Master data analysis basics.

Entry-Level Role: Begin as a Junior Data Analyst. Learn data cleaning, organization, and basic analysis.

Specialization: Deepen your expertise in a specific industry. Explore advanced analytics and visualization tools.

Advanced Analytics: Move up to Senior Data Analyst. Tackle complex projects and predictive modeling.

Machine Learning: Explore machine learning and data modeling techniques. Familiarize yourself with algorithms, and learn how to implement predictive and classification models.

Domain Expertise: Develop expertise in a particular industry, such as healthcare, finance, e-commerce, etc. This knowledge will enable you to provide more valuable insights from data.

Leadership Roles: As you gain experience, you can move into roles like Data Analytics Manager or Data Science Manager, where you'll oversee teams and projects.

Continuous Learning: Stay updated with the latest tools, techniques, and industry trends. Attend workshops, conferences, and online courses to keep your skills relevant.

Networking: Build a strong professional network within the data analytics community. This can open up opportunities and help you stay informed about industry developments.

Remember, your career path can be personalized based on your interests and strengths. Continuous learning and adaptability are key in the ever-evolving field of data analysis :)

If you can't find a data role, follow this path (that I tried and tested):

📍 1. Get skills (Excel, SQL, Power BI)
📍 2. Build projects
📍 3. Get a semi-data role (any role that only needs basic data skills e.g. Excel)

Heres what you should use your data skills for in this role:

📍 1. Help your team (eg. automate reports, build dashboards)
📍 2. Add this experience to your resume
📍 3. Share this experience online

This allows you to gain real world experience while practicing your skills

Here are the SQL interview questions:

Basic SQL Questions

1.⁠ ⁠What is SQL, and what is its purpose?
2.⁠ ⁠Write a SQL query to retrieve all records from a table.
3.⁠ ⁠How do you select specific columns from a table?
4.⁠ ⁠What is the difference between WHERE and HAVING clauses?
5.⁠ ⁠How do you sort data in ascending/descending order?


SQL Query Questions

1.⁠ ⁠Write a SQL query to retrieve the top 10 records from a table based on a specific column.
2.⁠ ⁠How do you join two tables based on a common column?
3.⁠ ⁠Write a SQL query to retrieve data from multiple tables using subqueries.
4.⁠ ⁠How do you use aggregate functions (SUM, AVG, MAX, MIN)?
5.⁠ ⁠Write a SQL query to retrieve data from a table for a specific date range.


SQL Optimization Questions

1.⁠ ⁠How do you optimize SQL query performance?
2.⁠ ⁠What is indexing, and how does it improve query performance?
3.⁠ ⁠How do you avoid full table scans?
4.⁠ ⁠What is query caching, and how does it work?
5.⁠ ⁠How do you optimize SQL queries for large datasets?


SQL Joins and Subqueries

1.⁠ ⁠Explain the difference between INNER JOIN, LEFT JOIN, RIGHT JOIN, and FULL OUTER JOIN.
2.⁠ ⁠Write a SQL query to retrieve data from two tables using a subquery.
3.⁠ ⁠How do you use EXISTS and IN operators in SQL?
4.⁠ ⁠Write a SQL query to retrieve data from multiple tables using a self-join.
5.⁠ ⁠Explain the concept of correlated subqueries.


SQL Data Modeling

1.⁠ ⁠Explain the concept of normalization and denormalization.
2.⁠ ⁠How do you design a database schema for a given application?
3.⁠ ⁠What is data redundancy, and how do you avoid it?
4.⁠ ⁠Explain the concept of primary and foreign keys.
5.⁠ ⁠How do you handle data inconsistencies and anomalies?


SQL Advanced Questions

1.⁠ ⁠Explain the concept of window functions (ROW_NUMBER, RANK, etc.).
2.⁠ ⁠Write a SQL query to retrieve data using Common Table Expressions (CTEs).
3.⁠ ⁠How do you use dynamic SQL?
4.⁠ ⁠Explain the concept of stored procedures and functions.
5.⁠ ⁠Write a SQL query to retrieve data using pivot tables.


SQL Scenario-Based Questions

1.⁠ ⁠You have two tables, Orders and Customers. Write a SQL query to retrieve all orders for customers from a specific region.
2.⁠ ⁠You have a table with duplicate records. Write a SQL query to remove duplicates.
3.⁠ ⁠You have a table with missing values. Write a SQL query to replace missing values with a default value.
4.⁠ ⁠You have a table with data in an incorrect format. Write a SQL query to correct the format.
5.⁠ ⁠You have two tables with different data types for a common column. Write a SQL query to join the tables.


SQL Behavioral Questions

1.⁠ ⁠Can you explain a time when you optimized a slow-running SQL query?
2.⁠ ⁠How do you handle database errors and exceptions?
3.⁠ ⁠Can you describe a complex SQL query you wrote and why?
4.⁠ ⁠How do you stay up-to-date with new SQL features and best practices?
5.⁠ ⁠Can you walk me through your process for troubleshooting SQL issues?