Data science is the process of using advanced analytics techniques and scientific principles to analyze data and extract valuable information for business decision- making, strategic planning and other uses.
By Charity Kashu
Specific Area In Data Science.
When you decide on getting started in data science, first look at the specific area of data science that interests you. Business analysis, Data analysis, Data visualization, Financial analysis, Healthcare analysis, Recommendation systems, Natural language processing and or Image processing and get involved in that particular area.
Understanding The Lifecycle Of Data Science.
The main job of Data Scientists is to address problems and construct models to make better decisions for business challenges. The following steps are involved in Data Science processes:
Defining Business Problem.
Data Collection and Preparation.
Exploratory Data Analysis.
Model Deployment and Evaluation.
Key Tools Used In Data Science.
Data Scientists rely on a number of specialized tools and programs developed specifically for data cleaning, analysis, and modelling. While there are a handful of statistical programming languages, R and Python are by far the most popular data science programming languages. R is built purposely for data analysis and data mining. Python is more widely used as a general purpose programming language that also happens to do well in data analysis operations. There are a number of other data tools and languages used in data science like the SQL, Jupyter Notebook, C/C++, Java, Scala, Excel, Tableau, MATLAB, Spark and TensorFlow. So if you don’t have any coding experience, you may take a look at some online courses that teach the programming language that interests you especially Python and R since they are the most popular choices for data science.
Always Read, Listen And Watch.
Make sure you read at least one or two articles, listen to a data science podcast or watch data science videos every day to stay current and get comfortable with the language of data science.
Find A Data Science Course.
Once you have started getting comfortable with your chosen programming language, start checking out for Data Science courses. Then start looking for scholarships, challenge, and competitions to get more information available out there.
Create your GitHub profile, clean up your GitHub profile then push commits every day if you can and future the best of your projects. Now start contributing to open source organizations on GitHub. Start writing articles on what you have learned, and this will help you understand concepts well.
Thanks for reading.
Top comments (1)
the importance of data science courses cannot be more stressed. it gives one a starting point filled with practical. great article!