Data Science roadmap

Overview

As a field of study involving statistical tools and techniques to extract meaningful insights from data, data science is becoming a critical element of modern-day business. Data Science techniques assist organizations in making informed decisions based on logic and reason rather than intuition alone.
Data scientists work with structured, semi-structured, and unstructured data to find patterns that help them solve problems and predict future events. Data scientists work in teams with other members of their organization. As data science is an emerging field, it offers opportunities for everyone with an interest in data and how it can be leveraged.
The world is changing and large organizations that adopt innovative ways to remain competitive are placing their strategic moves through a series of logic. In such organizations, the task involves analyzing large amounts of unstructured information i.e., text or images to find patterns that will enable businesses to improve their operations and increase profits.

Beginning as a novice

Data science is a multidisciplinary field that involves using scientific methods, processes, and systems to extract knowledge and insights from structured and unstructured data. It encompasses data exploration, feature engineering, model building, and visualization. This will involve learning programming languages such as Python and/or R, libraries, and frameworks like NumPy, Pandas, and sci-kit-learn.
In order to properly utilize the programming languages an understanding of the mathematical and statistical concepts that underlie many of the techniques used in the field is crucial. It includes topics such as probability, statistics, linear algebra, and optimization.

How to Start Learning Data Science as a Beginner?

Learning data science as a beginner involves learning the necessary tools and technologies, understanding the underlying concepts, and practicing and implementing what you have learned. With persistence and dedication, you can build a strong foundation in data science and become proficient in the field. So, if you are unsure about where to learn data science, given below is a step-by-step data science roadmap for beginners to help you get started on your pursuit.

1. Learn Query Language Like SQL
2. Programming Language Like R/ Python
3. Visualization tools like PowerBI/ Tableau etc.
4. Basic Statistics for Machine Learning
5. Machine Learning Algorithms
6. Practice and Implementation

Data Science Jobs Roles

Data scientists use their skills to understand the stories hidden in large datasets (sets of information). They can also help organizations develop new strategies and make more informed decisions by analyzing data from multiple sources. Below are some of the most common ones:
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1. Machine Learning Engineer
2. Data Engineers
3. Business Analyst
4. Statistician
5. Data Architect
6. Data Scientist

Conclusion

To become a data scientist, it is important to be familiar with the programming languages used most frequently in the industry and some major data-related concepts.