What’s the fastest way to learn to become a Data scientist?
In this guide, I’ll show you a proven but simple process that’ll turn you into a data scientist expert at lightning speed.
Follow me on the journey on how to become a data scientist.
What does a data scientist do?
- Careers in Data Science
- Data Analyst
- Business Analyst
- Machine Learning Scientist
- Final thought
The journey to becoming a data scientist may seem daunting, however how to become a data scientist is not as complicated as people may think and it’s possible to break into the field as long as the necessary steps are taken.
In common usage, data is the sum of information which can come in the form of text, observations, figures, images, numbers, graphs, or symbols.
Data conveys information, describing the quantity, quality, fact, statistics, other basic units of meaning, or simply sequences of symbols that may be further interpreted formally.
In IT (information technology), data is information that has been converted into a format that is efficient for processing, storage, and transmission for the computer.
This may be done by storing it in the form of electrical signals or recording it on magnetic, optical, or mechanical recording media.
In the field of IT, data is typically obtained from databases, but they can also be obtained from sources such as they can get the data by scraping data from websites, purchasing data from data providers, or collecting data from surveys, clickstream data, sensors, cameras, etc.
Data science is the field of study that involves the use of data to extract meaningful insights for business decision-making and strategic planning.
It is a multidisciplinary approach that combines principles and practices from the fields of mathematics, statistics, specialized programming, advanced analytics, artificial intelligence (AI), and machine learning with specific subject matter expertise to uncover actionable insights hidden in an organization’s data.
There are many reasons enterprises invest in data science teams, from being able to leverage data to find insights about their customers to finding loopholes in their business services and solutions and making processes more efficient to find ways to maximize profit as a business.
Related: Data Science Career Opportunity
How to become a data scientist in Nigeria
There is a lucrative job market for data scientists in Nigeria and other countries due to the increased usage of data and data technologies across various enterprises.
Depending on factors like one’s qualifications, level of expertise, and years of experience, a data scientist can earn between NGN 200,000 and NGN1.5 million in Nigeria, although entry-level roles may offer less pay.
Here are some steps to become a data scientist you may want to consider:
Step 1: Earn a bachelor’s degree
Obtaining a bachelor’s degree in a relevant field such as data science, computer science or statistics is a good place to start to become a data scientist.
While there are people who have reported having careers in data science without a degree, including it in your data science education and training plan can help give you a competitive edge in the job market. It is one of the most common criteria organizations look out for when hiring data scientists.
You can also consider going further in getting a postgraduate degree in areas such as data visualization, machine learning, and artificial intelligence.
Step 2: Gain knowledge of relevant programming languages
It is essential to brush up on relevant programming languages to become a data scientist.
Popular programming languages for data science include Python, R, SQL, and SAS. These are essential languages when it comes to working with large datasets.
Step 3: Sharpen other relevant skills
There are other skills required for data scientists that you will need to sharpen such as
Data visualization by learning the necessary tools that allow data scientists to communicate their findings from data effectively. Popular visualization tools include Microsoft Excel, Power BI, and Tableau.
Machine learning helps data scientists develop efficient and fast algorithms and data-driven models for the real-time processing of this data.
Big data makes it possible for data scientists to analyze a lot of data quickly and effectively, giving them an overview of more data. When hiring, some companies may want to see that you have some familiarity in grappling with big data. Some software frameworks used to process big data are Hadoop and Apache Spark.
Communication of data insights to relevant staff and stakeholders in your organization.
Step 4: Take a data science course
A comprehensive way to learn more details with regards to data science including the tools, techniques, and methods needed is by taking a data science course or program.
Some programs also offer the chance to learn with other people and take on real-life projects that will prepare you for working in the data science industry.
Many data science programs are available to get you started- in the classroom and also in e-learning formats. There are also data science programs in Nigeria that you can check out.
Step 5: Apply for an internship
Internships are a good way to get your foot in the door for a career in data science. You can seek positions that work heavily with data, such as data scientist, data analyst, business intelligence analyst, or statistician.
Through internships, you can apply theoretical knowledge gained in the real world, build your resume, improve job stability, expand on your skills, develop professional connections, and build your resume, amongst others.
Related: Data Science Career Opportunity
Step 6: Applying for an entry-level role
Once your internship is over, you can decide to apply to the organization you did your internship if vacancies are open or apply to another organization for an entry role in data science. From there you can gain experience as you go and work up the ladder as you expand your knowledge and skills.
What does a data scientist do?
Depending on the organization, job roles for a data scientist can vary from place to place. Sometimes they take on the tasks of data analysts, data engineers, and business analyst in places like startups where the capital and resources to hire a large number of employees is not available.
In large organizations however, they tend to work with a team that can include a data engineer, data science architect, data science developer, data analyst, business analyst, agile scrum master, and relevant professionals in the organization or the specific organization problem that needs to be solved.
A data scientist’s duties can include developing strategies for analyzing data, preparing data for analysis, exploring, analyzing, and visualizing data, building models with data using programming languages, such as Python and R, and deploying models into applications.
Some day-to-day activities of a data scientist might include
- Access and Collection Extraction of raw data from valuable data sources (data mining)
- Processing the data (structured and unstructured data)
- Data Cleaning and preparation to make the data suitable for analysis.
- Understanding and exploring data to find patterns in the data to use for data modeling machine learning models and algorithms.
- Communicating results and insights found through analysis and data science efforts to stakeholders.
- Sharing data insights with the business teams who will use it in their marketing efforts and other business efforts.
Careers in Data Science
Once you have taken the steps to become a data scientist, you can either apply directly for a job as a data scientist or these other careers in data science;
Data Analyst
Data analysts collect, clean, and interpret data sets to answer a business question or derive business insights from it. They can also help in supporting and monitoring databases for issues to report to the suitable team to respond to.
Business Analyst
Business analysts assess how organizations are performing and help them make their processes and systems more efficient. They conduct analysis and research to come up with solutions to business problems and help introduce these solutions to businesses and their clients.
They gather and analyze data to develop and investigate potential solutions – including improvements to systems and processes – to organizational challenges.
As businesses seek to increase efficiency and reduce costs, they seek business analysts to help them search for valuable information from their data that can achieve this means.
Machine Learning Scientist
A machine learning scientist focuses on researching, designing, and implementing complex adaptive algorithms that drive AI systems and building models, working in collaboration with data scientists, data engineers, and algorithm specialists.
They also develop autonomous AI software and conduct tests to ensure that the software generates accurate predictions as much as possible.
Final thoughts
In conclusion, the process of how to become a data scientist may take time, but it is worth it if you are interested in building a career in this field.
The amount of data retrieved by organizations continues to increase across different industries as well as the demand for data-driven technologies to help in proper management of this data.
Organizations are also seeing that valuable insights to maximize profit can be derived from data so they are seizing this opportunity which means there’s a likelihood of increased demand for data scientists in the future.
