# @woman.engineer on Instagram

- **Type:** Video
- **Original URL:** https://www.instagram.com/p/DR7BROpiN9B
- **Gondola URL:** https://gondola.cc/posts/61845502-womanengineer-instagram
- **Thumbnail:** https://img.gondola.cc/tr:w-,h-,fo-auto/postThumbnails/20831fee30.jpg
- **Posted:** 2025-12-06T12:35:18.000+00:00
- **Account Owner:** Zeynep Küçük  Woman Engineer (@woman.engineer) — https://gondola.cc/woman.engineer

## Caption

📍Learning to code and becoming a data scientist without a background in computer science or mathematics is absolutely possible, but it will require dedication, time, and a structured approach. ✨👌🏻

🖐🏻Here’s a step-by-step guide to help you get started:

1. Start with the Basics:

- Begin by learning the fundamentals of programming. Choose a beginner-friendly programming language like Python, which is widely used in data science.

- Online platforms like Codecademy, Coursera, and Khan Academy offer interactive courses for beginners.

2. Learn Mathematics and Statistics:

- While you don’t need to be a mathematician, a solid understanding of key concepts like algebra, calculus, and statistics is crucial for data science.

- Platforms like Khan Academy and MIT OpenCourseWare provide free resources for learning math.

3. Online Courses and Tutorials:

- Enroll in online data science courses on platforms like Coursera, edX, Udacity, and DataCamp. Look for beginner-level courses that cover data analysis, visualization, and machine learning.

4. Structured Learning Paths:

- Follow structured learning paths offered by online platforms. These paths guide you through various topics in a logical sequence.

5. Practice with Real Data:

- Work on hands-on projects using real-world data. Websites like Kaggle offer datasets and competitions for practicing data analysis and machine learning.

6. Coding Exercises:

- Practice coding regularly to build your skills. Sites like LeetCode and HackerRank offer coding challenges that can help improve your programming proficiency.

7. Learn Data Manipulation and Analysis Libraries:

- Familiarize yourself with Python libraries like NumPy, pandas, and Matplotlib for data manipulation, analysis, and visualization.

For more look at the comment ⤵️
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#datascience #computerscience #datascientist #dataanalytics #dataanalyticstraining #python #softwaredeveloper #dataanalysis #bigdata #generativeai #codingbootcamp #businesswoman #veribilimi #codemotivation

## Stats

- **Views:** 8,206
- **Likes:** 1,396
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- **Comments:** 32

## Tags

python, computerscience, datascientist, dataanalysis, generativeai, datascience, businesswoman, bigdata, codingbootcamp, codemotivation, dataanalytics, veribilimi, softwaredeveloper, dataanalyticstraining

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