In recent years, data science has been applicable in every industry. From preparing data that can be analysed, to aggregating data to receive insights that can help organizations perform better - a data scientist's work is varied and in demand. Therefore, candidates looking to work in the field can opt for a data analytics course with placement. Interested individuals or even working professionals who wish to change careers can learn data science from Imarticus Learning. The institute provides online courses in data science and analytics as well as machine learning and prepares students for the professional sphere.
To land a job as a data scientist, every candidate needs a portfolio. A data science portfolio documents the candidate's skills and abilities. It can be accessed by employers to understand what experience the candidate has.
Build the Best Data Science Portfolio
Students pursuing a data science course or a PGA in data analytics will need to put together a portfolio before interviews. This can be done in just 5 steps.
Step 1: Make a List of All Available Jobs
Once a student has completed the data science program or DSP, they can begin to look for jobs. Imarticus Learning is an institute that offers placements. Students need to check what the jobs require and prepare the portfolio accordingly.
Step 2: Select Project Ideas
The best courses in data science will train students to come up with innovative projects. Projects should showcase the candidate's problem-solving skills and the ability to formulate insights that are actionable from a volume of data.
Step 3: Find Datasets
To solve issues and create actionable insights, datasets are necessary. While creating the portfolio, the candidate must look for messy datasets that need to be cleaned up, especially because this is one of the primary tasks of a data scientist and most companies will require such skills. There are many data repositories available online that provide datasets for free.
Step 4: Showcase and Document Skills
While completing the project, candidates should remember to thoroughly document all actions taken. It is necessary to choose a project that allows one to showcase every skill, especially those that potential employers require. The focus should be on problem-solving through various approaches, researching supplemental information, and using data analytics to create actionable insights.
Step 5: Expand to Include More Projects
Those who learn data science will be trained in advanced skills like machine learning and data visualization. To showcase such a range, a candidate should include more than one project in their portfolio. The ability to handle complex projects will impress employers.
Things to Remember While Creating A Data Science Portfolio
A data science portfolio needs to be effective and comprehensive. To create such a portfolio, students and potential candidates should keep in mind the following points.
- Projects done while in school can be included in a portfolio. Students enrolled in Imarticus Learning's best courses in data science can document their Capstone Projects.
- The portfolio should be accessible. It should be available to employers as well as peers so that they can provide feedback.
- The list of projects in the portfolio should be independent. Overlapping project topics can prove to be confusing and irrelevant.
- The projects should be highlighted so that they can be easily located. Online repositories with public source codes can be used for this.
Completion of a data analytics course with placement from Imarticus Learning will open many doors. Students will be able to tackle industry-level projects and provide documentation on their portfolios. A well-planned portfolio will ensure a secure job as a data scientist.