How to add Data Science Training Course Certificate in Resume

If you are still wondering how Data Science will change the future, then the fact of the matter is that it has made significant strides in every business niche in recent years. Data Science is one of the most lucrative career opportunities, thus triggering the demand for Data professionals. Data Science encompasses several other technologies like Artificial Intelligence, Machine Learning and more. Hence, having these skill sets will help you excel professionally. Enrolling on the Data Science Certification Course Online is the right way to start a career in this domain.

What is Data Science?

It is an interdisciplinary domain that studies the data and derives useful insights. Data Science also incorporates several other principles like mathematics, statistics, computer engineering, Artificial Intelligence, and others.

We are creating more data than ever. Today, on average, we create 2.5 quintillion bytes every day. This clearly highlights the penetration of the Internet. With the growing use of connected devices, the volumes of data we will create will be even more. Hence, the relevance of Data Analysis increases. Here comes the role of qualified and skilled data professionals. With the Data Science training course certificate, you will be equipped with all the Data Science skill sets and expertise in the allied concepts. Having this skill set as a part of your resume will ensure better job prospects and higher pay. So, if you are wondering how to add a Data Science training course certificate to your resume? Read ahead.

What are Data Science Training Certification Courses?

One of the easiest ways to add the Data Science certificate to your resume is by enrolling online in the Data Science certification course. Having a certification in this domain is an additional skill set. Since this field is evolving, there will be a growing demand for Data professionals. The Data Science course and certification train the individuals for the real-world setup.  These programs are designed in tandem with industry demand. Some of the key features of this course are:

Key Features of Data Science Certification

Comprehensive Curriculum

Another notable feature of the best Data Science certification course is its comprehensive learning module. Thus, it focuses on providing all the fundamental concepts of Data Science and light concepts of Machine Learning, Artificial Intelligence, programming languages and others. Usually, a Data Science course comprises topics on statistical analysis, data visualization, data mining and data preprocessing.

Practical Hands-on Approach

The focus of the best Data Science certification course is to equip the students with all the knowledge and skills that will help them in the real-world setup. And so, the Data Science courses provide hands-on exercises and real-world case studies. The students get to work on module-specific case studies and present their ideas. This eventually helps them gain experience in solving real-world problems.

Industry-relevant Skills

When choosing a Data Science course online certificate program, you should check if it focuses on teaching industry-relevant skills. Today the application of Data Science is not limited to just one industry. It finds multidisciplinary applications. Hence a curriculum that focuses on nurturing industry-relevant skills like Machine Learning algorithms, data visualization, building dashboards, data interpretation and presentation will help you land a better-paying job.

Experienced Instructors

The team of instructors also plays a significant role in defining the relevance of the Data Science course. A platform that offers learning from practising Data Scientists helps you gain better insights into the industry. Also, it promotes better comprehension of the concepts of Data Science and its application.

Flexibility and Accessibility

Today online Data Science courses are prevalent. This is primarily because most of the professionals are also now transitioning into this domain. Hence you must look for a course that offers flexibility in learning and ease of accessibility. Most e-learning platform gives you lifelong access to the course material, which helps you in keeping yourself updated with the concepts.

Capstone Projects

Many Data Science courses offered include a capstone project. Here the learner gets to apply their skill sets to a real-world problem. Solving such issues using conceptual expertise helps in gaining confidence and makes an individual job ready. This project also makes the learner demonstrate their understanding of Data Science concepts and showcase their learning ability to solve complex problems.

Career Support

Career support and placement assistance or yet another set of features offered by the Data Science course provider. With the placement assistance, job guarantee programme and pay after placement features, the learner has the confidence that they can easily transition into Data Science roles or advance their careers in the field.

Continuous Learning

The Data Science domain is evolving, and the best Data Science course will always emphasise providing updated knowledge and skills. Check if the course provider organizes hackathons and Datathons. These platforms not only become a ground to test your skills but also helps you network with the individuals in your domain. All this eventually helps in boosting the career.

Listing online Data Science course on your resume: A step-by-step guide

When preparing your resume, your prime focus should be on the following categories:

Data Science Resume Job Description

As a Data Scientist, your resume is your ticket to landing your dream job. A well-crafted job description in your resume can make a significant impact in drawing the attention of potential employers and showcasing your skills and experience. Here are some key tips on how to create an effective job description for your Data Science resume:

Start with a Strong Title

Focus on making your resume clear and concise. For example, you can use standard job titles like Data Scientist, Data Analyst or Machine Learning engineer. This ensures that your resume is easily understood by the recruiter, and they can filter your profile as per the desired role.

Highlight Your Key Responsibilities

Always focus on providing a brief overview of your primary responsibilities as a Data Scientist. This may include tasks such as Data Analysis, statistical modelling, Machine Learning algorithm development, data visualization, and data-driven decision-making. Always focus on using action verbs to describe your contributions to the achievements.  Here is what you need to add to your resume


Analysed Built
Conducted Created
Collaborated Developed
Integrated Led
Managed Partnered
Support Designed

 Showcase Your Technical Skills

 In addition to using the right words and phrases in your resume, you should also highlight the key skills. These include the following :

Python Machine Learning
Data Visualization Data Analytics
Data Management Data-driven Decision Making
Deep Learning Hadoop
Predictive Modelling Tableau
Business Intelligence Risk Analysis


Tailor Your Resume as Per the Job

 Today, people blindly rely on ChatGPT for every solution; you should not blindfold and trust this tool. Make sure that you customize your resume per the job’s demand. Carefully crafting the resume to suit the job description will improve the selection prospects.

Keep it Concise and Easy to Read

Do not make things complex; your resume should be crafted to instantly capture the reader’s eyes. Hence, concise and crisp should be the watchword when designing the resume. Use a clear and professional font, and proofread your job description to avoid grammatical or typographical errors.

Showcase Your Data Science Skills and Projects

If you plan to transition into the Data Science domain, your resume will represent your skill sets and expertise. Hence you must focus on showcasing Data Science skills and projects you have undertaken as a part of your learning journey.

The focus should be to add the different projects that you have done. For this, you can extract the data sets from the sources like Kaggle and work on them. For example, some of the projects that you can add to your Data Science portfolio are:

  1. Sentiment analysis
  2. Movie preferences
  3. Stock market prediction
  4. Business Insights

 Adding these projects to the resume is to showcase to the recruiter that you have the necessary skill sets suitable for the job role.


The resume should be built in a way that instantly gets the attention and showcases your skill sets. The tips mentioned above will help you in the same. You can refer to these pointers when preparing your resume.


What is the purpose of the resume?

The purpose of a resume is to highlight your skill set and expertise. A well-defined and structured resume instantly gives the recruiter a glance at your expertise. Adding the skill sets like Data Analysis, Data Science, Machine Learning, and Artificial Intelligence will give you a competitive edge.

How Do I List Pickl.AI Data Science Online Certificates on My Resume?

Your resume should showcase your efficiencies. Only a well-crafted resume will be able to catch the eyes of the recruiter. Since Pickl.AI’s online Data Science certification allows you to work on different case studies and projects, it helps build up the profile. Also, it showcases your expertise in handling real-world cases. This will increase your prospects of bagging the job. Pickl.AI has one of the best certification courses for Data Science that encompasses both theory and practical learning.

How can I Apply for Online Data Science Certification Course at Pickl.AI Associated with TransOrg Analytics – A Top Data Scientist Company?

You can log on to Pickl.AI. Here, you will get a list of Data Science courses. Choose the one that matches your aptitude. To proceed, adding your details is a must. Once you have filled in the details, the team Pickl.AI will contact you for the next steps.

Aishwarya Kurre

I work as a Data Science Ops at and am an avid learner. Having experience in the field of data science, I believe that I have enough knowledge of data science. I also wrote a research paper and took a great interest in writing blogs, which improved my skills in data science. My research in data science pushes me to write unique content in this field. I enjoy reading books related to data science.