A journey of thousand miles begins with a single step -Chinese Proverb

Are you interested to become a Data Scientist? Take up this Data Science Roadmap Test and assess your level of understanding!

What does Data Scientist do?
Data scientist are responsible for extracting insights and knowledge from data through a combination of statistical analysis,data mining,visualization and machine learning.
They work on complex problems and uses data to inform decision making.

If you would like to learn data science,here is your general roadmap to guide your journey on data science:

1. Programming skills

Gain proficiency in a programming language such as Python or R which is most commonly used in data science.
Learn and understand fundamental basics such as data types,variables,data structures and algorithms.
Gain deep understanding of SQL(Structure Query Language) to manipulate database.

2.Machine Learning

Learn and understand fundamental concepts of machine learning algorithms such as supervised ,unsupervised and reinforced machine learning algorithms.

3.Mathematics and statistics

Have a strong foundation in mathematics such as linear algebra,probability and calculus as well as statistics concept such as regression analysis and hypothesis testing.

4.Data Visualization and manipulation

Learn and understand visualization tools such as Tableau,Power BI and its libraries to communicate insights effectively.

5.Data preparation and gathering
Learn and understand ETL techniques i.e(Extract,Transform and Load) for data processing.
learn and understand data collection from various sources such as web scrapping,data pipelines,API's and databases.

6.Model Building and Deployment

After learning machine learning,build machine learning models,validate them using appropriate techniques and deploy them using web frameworks such as Django,Flasks or FastAPI.

7.Cloud Platform and Version Control

Explore to various cloud platforms such as Microsoft Azure,AWS and Google Cloud for scalable data processing.
Lastly,learn and understand how to use version control system such as Git to collaborate and track changes to your projects.

Remember that the roadmap is flexible, and you can adapt it based on your goals, interests, and the specific requirements of the data science field you want to enter.

Continuous learning,networking,collaboration with other data scientists and practical experience are key components of a successful data science career.