Data Science for Absolute Beginners: 2023-2024 Complete Roadmap
Tags: beginners, datascience, community
Published: 2023-10-01 14:00:00

## Introduction

If you're looking to solve real-world problems with data as your superpower, then you're ready to kickstart your journey in the field of data science. The world of data is as wide as your imagination and as a data scientist, the number of '_crimes_' you can solve are limitless.

If you're going to be a data scientist then surely you must know what data science is. Data Science uses scientific methods, processes, algorithms and systems to extract knowledge and insights from structured or unstructured data. Simply put, data science involves creating new ways of modeling and understanding the unknown by using raw data-getting something new from what exists. 

In this article we'll have a step by step guide to get started in this field as a beginner, with or without a tech background. This guide will help you gain the confidence to dive into the amazing world of data, take up the challenge and use your skills to make an impact.

## Roles of a data scientist

A data scientist is a magician, they take existing data and turn it into new features and models. Here are some of the roles you might take on as a data scientist:

**1. Data Collection and Preparation**- this involves collecting data from various sources cleaning it, removing outliers and transforming it into a format that can be used in the chosen analytical tools.

**2. Data Analysis** -using a variety of statistical and machine learning techniques to perform hypothesis testing, visualize data and extract insights to identify patterns and trends.

**3. Feature Engineering** -transforming raw data into features that are more informative and useful for machine learning models by selecting, creating and transforming existing features to extract more value from the data.

**4. Model Development and Deployment** -using machine learning algorithms to train models on historical data and integrating these models into production systems.

**5. Communication and collaboration** -writing reports, giving presentations and working with stakeholders to develop data-driven solutions.




## How do I get started?

 **Step 0: Stop Looking Up More Roadmaps**
You've been scrolling on the internet looking up how to get started in this field. The anxiety is lying to you, you already have enough information on what you need. Just start!

**Step 1: Learn the basics of Programming and Data Manipulation**

- Python is recommended to use in data science as it is easy to learn and has a wide range of libraries available.
- SQL is a query language  used to interact with databases. It is used when extracting and cleaning data.

**Step 2:Learn about Statistics and Machine Learning**

- Familiarize yourself with statistical concepts such as probability, distributions and hypothesis testing.
- Machine learning allows computers to learn from data without being explicitly programmed. Data scientists use machine learning to build models that can make predictions or decisions.

**Step 3:Learn about data visualization**

- Interact with tools for transforming data into visually appealing and understandable representations which can be used to communicate findings to stakeholders.

**Step 4:Build projects and practice your skills**

- Best way to learn is by doing. Practice your skills and learn new techniques to better your craft.
- Utilize the available online resources for practicing data science skills.

**Step 5:Network with other data scientists**

- Networking is a great way to learn new things and stay up-to-date with the latest trends in the field.
- Join an online community or a school club. More is fun!

After mastering the basics and once you are comfortable that you have a solid foundation in data science, you are ready to specialize in a particular area or even apply for data science jobs.

Ready, Set, and Begin!