Data Science Road Map for Beginners 2023/2024

Data science is one of the fastest-growing careers in the IT sector, with a lot of untapped potential. According to a report by LinkedIn, the career is expected to grow to $230.80 billion by 2026 from $37.9 billion in 2019. Should you enroll for a bachelor's degree or take the shortest route in learning data science? If you choose the latter, this is a beginner's road map to learning data science.
Road map
Since the data science field is quite broad, a road Map makes learning relatively easy and objective and even guides the learner on the critical concepts that would help them land their first job.
Programming
The first step in learning data science is learning a programming language. There are lots of programming languages that you can learn, and they include Python, R, Java and SQL. As a starter, I first chose to learn Python and SQL since I find them easy to understand and remember.
Math fundamentals
The second step would be learning math fundamentals. Remember that data science involves dealing with numbers and learning to interpret the data, and thus, the basic math fundamentals you should know are statistics, linear algebra, differential calculus and discrete math.
Machine learning
Machine learning would be the next step, which entails solving problems using algorithms developed by human programmers. In this part, you should learn about regression,
classification and clustering, and also feature engineering.
Deep learning
Deep learning is another concept you must learn, which will entail learning about PyTorch, TensorFlow, binary classification, artificial neural networks, and Keras. Deep learning is a subset of machine learning that teaches computers to do what comes naturally to humans. The 'deep' in deep learning entails using multiple layers in the data networks.
Data visualization
Data visualization is the other step that entails transforming data into visual content, which is easier to interpret. The most common data visualization is Excel, which you have interacted with in the past. Other tools that can be used for data visualization include Tableau, Power BI, Qlik View, and Qlik Sense.
Data storage
Data storage tools are crucial to learning about management systems and databases like MYSQL, MongoDB, and PostgreSQL.
Deployment
Lastly, you must learn about cloud computing platforms such as Azure, AWS, and Google Cloud.
After learning, you must do projects and share them with potential employers and even fellow developers. Therefore, you must create a GitHub profile, a company that offers cloud-based storage and Git repository hosting services. This is also the platform where the potential will find your profile and hire you based on your projects.