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### Key points in this Admissions Team blog post:

**What is the Data Science Fellowship assessment exam?**

- 2 Parts of the assessment exam

- 3 Ways to prepare for the assessment exam

**What are the topics covered by the assessment exam?**

- Excel knowledge

- Python Programming

- Numerical Reasoning (Statistics)

- Graphical Analysis

- Algebra

- Analytical Thinking (Logic)

- Business Aptitude

## What is the Data Science Fellowship assessment exam?

### 2 Parts of the assessment exam

**Part 1**- Timed (60 minutes to complete), multiple choice format

**Part 2**- Untimed, essay portion with questions focusing on your intentions for joining the bootcamp

**both parts are required for a complete application.**

### 3 Ways to prepare for the assessment exam

**Aral-Aral for Data Science prep course**

The moment you sign up for the Data Science Fellowship, you will receive access to a free prep course with modules containing Python and Statistics content. Though it is not required to complete the prep course to proceed with your application, you might find the mini quizzes and notes we’ve provided helpful before you tackle the assessment exam.

**Review Sessions**

While going through the Aral-Aral prep course is a more self-paced and solo learning endeavor, attending Review Sessions is a more participatory way of reviewing for the assessment exam. In these sessions we gather bootcamp applicants and walk them through the exam coverage in real-time. There’s also Q&A time with the instructor who serves as the host of the review session.

**Viewing the exam coverage**

## What are the topics covered by the assessment exam?

### Excel Knowledge

Microsoft Excel is a basic data management tool that all learners should be proficient in prior to the bootcamp.**Q: What about Excel will be asked in the assessment exam?**

A: Spreadsheet Operations, Formulas, and Data Wrangling

These questions will give us an idea on your confidence level in using Excel.

### Python Programming

Python is an open-source, general purpose, and object-oriented programming language that is both simple and powerful for data scientists all over the world. The thriving Python community has already created over 100,000+ Python libraries. These libraries are all useful in helping data scientists face massive amounts of data and conduct their machine learning, data visualization, data cleaning, and data analysis tasks with ease.**Q: What about Python Programming will be asked in the assessment exam?**

A: Data Types & Structures, Control Structures, Functions

These questions will reassure us that you have a grasp on the fundamentals in order to manipulate data with Python.

### Numerical Reasoning (Statistics)

Statistics is a branch of mathematics that allows data scientists to uncover and analyze trends or patterns in data. Familiar terms like mean, median, and mode fall under descriptive statistics, which is more focused on producing a summary of what is present in the data set. On the other hand, inferential statistics, which helps us make predictions and draw conclusions from the data, cover concepts such as hypothesis testing, statistical significance, p-value, and more.

**Q: What about Statistics will be asked in the assessment exam?**

A: Descriptive statistics, Inferential statistics, Probabilities

These questions will show us how prepared you are to delve into the more advanced level of statistics tackled in the bootcamp.

### Graphical Analysis

Data visualization using Matplotlib is one of the key topics we’ll be teaching you in the bootcamp to create your first machine learning project. Matplotlib is a Python library used for creating visualizations that can be static, animated, and even interactive. If graphs are visual representations of data, then it’s imperative for you to have a sufficient understanding of them before entering the bootcamp.**Q: What about Graphical Analysis will be asked in the assessment exam?**

A: Visual Communication, Structure of Graphs, Grammar of Graphics

These questions will tell us if you’re able to understand data stories through visualizations, support or validate assumptions made, and communicate findings effectively.

### Algebra

Data sets are sometimes presented in matrix form. That is essentially why understanding the relationships between variables and modelling real-world functions mathematically are two core skills for learners of data science.**Q: What about Algebra will be asked in the assessment exam?**

A: Algebra Functions, Ordinary Differential Equations, Linear Algebra

These questions will reveal your comfort level in mathematical concepts for data science.

### Analytical Thinking (Logic)

Being able to think logically is a key precursor to succeeding with programming languages and other tools used in the field of data science.**Q: What about Analytical Thinking will be asked in the assessment exam?**

A: Process Flows, Conditional Logic

These questions will determine your ability to keep up with the data science tools we’ll introduce to you in the bootcamp.

### Business Aptitude

Data science is all about deriving the most value from data. Every industry—whether it be in e-commerce, healthcare, manufacturing, entertainment, and more—has its own set of business questions that can be answered by the insights uncovered by data scientists. Having the ability to make sense of business needs and situations allows data scientists to channel their technical skills in effective and value-adding ways.**Q: What about Business Aptitude will be asked in the assessment exam?**

A: Business Frameworks

These questions will signify your capability in providing meaningful insights, observations, and platform/design features that you can best apply in your career.

#### WAYS TO REACH US

- Send us an email at admissions@eskwelabs.com.
- Message us through the Eskwelabs Facebook Page.
- Sign up for a 1-on-1 consultation with Viv, our Admissions Associate, to discuss any concerns about these features. Book a 15-minute consultation here.

#### RECOMMENDED NEXT STEPS

**Updated for Data Science Fellowship Cohort 10**| Classes for Cohort 10 start on September 12, 2022.

**If you’re ready to dive in****Enroll**in the Data Science Fellowship via the sign up link here and take the assessment exam.**Note:**The assessment exam is a key part of your application. The deadline for the assessment is on August 21, 2022.

**Join**a Data Science Assessment Review Session before taking the exam.

**If you want to know more****Read**a more detailed guide on the Fellowship.**Attend**our free Open House event.**Book**a 15-minute consultation with Viv, Eskwelabs’ Admissions Associate.

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