Data science is the study of data in order to extract meaningful insights from it. It extracts insights by combining various subjects such as math and statistics, specialized programming, advanced analytics, artificial intelligence (AI) and machine learning. These insights are then used by organizations in decision making and strategic planning.
A data science roadmap is visual representation of a strategic plan designed to help one learn about and succeed in the field of data science.
As a wide field in technology, data science has several career paths one can follow:
Data Analyst - Collects, cleans and analyzes data.
Data Scientist - Builds predictive models and creates data driven solutions.
Data Engineer - Builds infrastructure for generation, storage and retrieval.
BI Analyst - Creates reports, dashboards and visualizations
Machine learning engineer- Implements ML algorithms and models.
NLP Engineer- Focus on understanding and interpreting natural languages.
Key Data Science skills for beginners
- Mathematical and Statistical Skills
- Programming Skills
- Communication Skills
- Curiosity
Mathematical and Statistical skills
Statistics - This is a branch of mathematics that teaches us how to collect and analyze data so that we can find answers to questions.
- Descriptive Statistics- Conducts experiments on the entire dataset
- Inferential statistics- conducts experiments from a small dataset then applies to the entire dataset.
Probability- Numerical representations of the likelihood of an event.
Calculus- Calculus is a branch of mathematics that deals with the study of rates of change and the accumulation of quantities. It has two main branches:
Differential Calculus - Differential calculus helps us understand how things change. It helps us understand how a function behaves at a single point
Integral Calculus - Integral calculus helps us find areas and accumulate quantities.
Linear Algebra
This is a branch of mathematics that deals with vectors and matrices.
PROGRAMMING SKILLS
SQL(Structured Query Language)- This is a an organized collection of data that handles large datasets.
Python programming - Python offers built in data structures and libraries that store and manipulate data efficiently.
- lists
- Tuples
- Dictionaries
- Sets
- Strings
Data Analysis and Visualization
Being a data scientist would require you to work on data visualization to display the pictorial forms of charts and graphs that can be easy to understood. There are hefty of tools that are being used and some of the popular ones are:
- Tableau
- Power BI
- Looker Studio
- Python Libraries e.g. Matplotlib, plotly
Communication Skills
Ability to spread and influence ideas that are easy to understand and that can be used in decision making.
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