DataCamp is one of the leading websites in the field of Data Science, Machine Learning, and Deep Learning and it always strives for improvement and development as competition grows with other self-learning platforms. Recently they launched the DataCamp summer challenge which is a process that consists of three stages. In each stage, there will be an assessment.
The certification ensures that the candidate has the knowledge, skills, and abilities to perform a Data Scientist role. These included but were not limited to:
Data Management:
Getting
data from a range of appropriate sources and resolving data issues, such as
formats, handling missing data, reshaping and joining, and validating data.
Exploratory Analysis:
Using
standard manipulation and visualization techniques to learn more about the data
available and insights that may be gained. Preparing data for further analysis
and modeling including the creation of new features.
Statistical Experimentation:
Using
data and relevant statistical approaches to perform experiments.
Model Development:
Developing
predictive models using appropriate machine learning techniques for the data
and task at hand. Performing all elements of the model development workflow
from initial fit to model validation and parameter tuning.
Coding for Production Environments:
Being
able to write reusable code to solve data problems. Identifying when problems
have occurred and resolved them effectively, ultimately resulting in a process
suitable for production environments for solving data challenges.
Communication and Reporting:
Presenting
data in reports or dashboards to make available to stakeholders and clearly
presenting actionable analytic results to business problems.
So,
let’s dive deeper and have an in-depth insight into each stage.
Stage (1): Timed assessments
Each assessment is a series of questions on a range of
topics to establish that the individual has the basic knowledge required for a
data scientist role. They use the adaptive testing approaches to understand to
a high degree of confidence the skill level of individuals who take the
assessments. There are three assessments; each of them covers a topic as
follows:
- Programming: to test coding for production (15 questions) each question should be solved in one minute or less. Passing score: 160.
- Statistics Fundamentals: to test statistical experimentation (15 questions) each question should be solved in one minute or less. Passing score: 155.
- Data Analysis in SQL (PostgreSQL): to test exploratory analysis (15 questions) each question should be solved in one minute or less. Passing score: 150.
There are scores given at the end of each assessment and you
should get the passing score at least. If you failed an assessment you can try
again until you pass. There is no limit on the number of attempts.
Stage (2): Coding challenge
The coding challenges are a free form, where candidates are
presented with certain data, but it is up to them to come up with an
appropriate solution. The goal of this task is to demonstrate that the
individual can perform the tasks required of them as a data scientist without
being guided towards the appropriate solution.
The coding challenge should be done in 90 minutes. However,
the task is not timed, and you can spend more time as you want to
finish the task.
Stage (3): Case study submission
The final stage of the certification required the individual
to complete a case study. This stage of the certification is graded manually
and stringently by DataCamp data scientist experts.
The case study is split into two parts:
- -
Technical report:
In the case of the technical
report, the audience is a data science manager. It can be considered that the
work is being presented to show how the task has been approached, why certain
actions were taken, and how work helps to solve the problem defined. There
is no one right answer.
- -
Non-technical presentation:
The final stage was to adapt the
information towards a non-technical audience. It is a common requirement for
data scientists to have to present their work to others who have no background
in data science. These audiences are interested in why the work was done and
what the outcome was, typically not how it was done.
The exam will be proctored by one of the DataCamp experts. The
exam duration is 4 hours. You will be given two hours only to finish the task
and prepare the presentation. After this, the exam invigilator will inform you
by your turn like if you are the first then you only have two hours but if you
are the last, then you have to wait until the end of the second two hours. Most
probably there will be 8 individuals taking the exam with you.
The task in brief is about building a model and provide a
presentation for the findings. It is quite easy for someone how finished the data
scientist track on DataCamp to complete the task.
From my point of view, the challenge was in the presentation using the proper words to address the non-technical audience.
In conclusion:
Pros:
- - The certification may be a great addition to your resume and to show off your skills; especially the certificate is exam-based and not just a course you complete.
- - After finishing the certificate, you will get some career coaching such as an interview one-on-one with a career coach from DataCamp and invitations to external websites that has a kind of cooperation with DataCamp to get your resume polished and to train you on the technical interview.
- - Suitable for entry-level data scientists and those who pursue a career in data science.
- you are free to use Python or R in the tasks.
Cons:
- - You should be on the premium plan to proceed to the next stages after the first stage.
- - The certificate expires after two years.
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