One question we get a lot is, “What’s the difference between the Data Science Fellowship and the Data Analytics Bootcamp?” Aside from the main focus of both programs being obvious in their name (data science and data analytics), there are other considerations that people have when choosing which program to enroll in.

Key points in this Admissions Team blog post:

Comparing the Data Science Fellowship and the Data Analytics Bootcamp
  • Schedule and Duration
  • Curriculum
  • Graduation requirements
  • Qualifications
  • Tuition fee and Payment methods
  • Study Now, Pay Later feature
  • Scholarships
  • Job guarantee and Job interview guarantee features

We believe in giving you the details you need to make an informed decision between the two programs. Let’s tackle each of the key points above one by one.

Schedule and Duration

Schedule and Duration differences between the Data Science Fellowship and the Data Analytics Bootcamp
Data Science Fellowship
Data Analytics Bootcamp
  • Schedule: Mondays to Fridays + Saturdays
    • Weekdays: 6:00 - 9:00 PM
    • Saturdays: 1:00 - 4:00 PM
  • Duration: 12+ weeks
  • Schedule: Mondays, Wednesday, Fridays + Saturdays
    • MWF: 6:00 - 9:00 PM
    • Every other Saturday: 1:00 - 4:00 PM
  • Duration: 8 weeks

Curriculum

These are what our Fellows (Data Science Fellowship) and Analysts (Data Analytics Bootcamp) will be learning in the programs. Please note that the two programs have their own schedules.

Curriculum differences between the Data Science Fellowship and the Data Analytics Bootcamp
Data Science Fellowship
Data Analytics Bootcamp
Creating Your First Machine Learning Project
Begin your data science journey by deploying your very first data app! In this group sprint, you will learn how to obtain insights and create data stories by clustering geographical data.

    KEY TOPICS
  • Data Wrangling with Pandas
  • Data Visualization with Matplotlib
  • Unsupervised Machine Learning
  • Create data apps using Streamlit
  • Create and manage your own git repository on Github
CO2 Emissions Dashboard and Presentation
Use PowerBI to design a dashboard that investigates the movement of CO2 data, with dynamic dashboard elements and beautiful visualizations.

    KEY TOPICS
  • Introduction to Analytics
  • Data Analytics Pipeline
  • Data Validation, Cleaning, and Visualization with PowerBI
  • Descriptive Analytics
  • Dashboarding with PowerBI
  • Storyboard
Building Your Own Spotify Recommender Engine
Netflix, Amazon, Facebook, and many other online services, use our data to suggest other products we might like. In this sprint, we will build a Spotify recommender system using features of songs to recommend new music.

    KEY TOPICS
  • Supervised Machine Learning (Linear Regression and KNN)
  • Data Mining using API
  • Building Recommender Engines
Company Deep Dive with SQL
Explore the product performance and sales of a company, mastering the queries, joins, and syntax of SQL along the way.

    KEY TOPICS
  • Introduction to SQL
  • Fundamental Queries (e.g. SELECT, FROM, etc.)
  • Aggregations (e.g. COUNT, AVG, etc.)
  • Intermediate Queries Pt. 1 (e.g. WHERE clause, GROUP BY, etc.)
  • Intermediate Queries Pt. 2 (e.g. JOINS, Manipulating dates)
  • C.R.U.D.
Working with Big Data: Real-Time Credit Fraud Analysis Using Spark
Banking industries are facing severe challenges in the form of fraudulent transactions. In this sprint, we will implement a detection system that can identify credit card frauds in real-time.

    KEY TOPICS
  • Supervised Machine Learning (Tree-based and Ensemble Models)
  • Work with common cloud infrastructures
  • Analytics engine for big data
Company Business Review
Conducting a real-life company review that will lead to actionable recommendations and insights. The last two sprints are opportunities for our learners to interact with external stakeholders. That is why the topics for these sprints depend on the direction and feedback of the stakeholder or company after initial presentations.

    KEY TOPICS
  • Analytics engine for big data
  • Analytical Frameworks (e.g. Business Context Diagram, etc.)
  • Diagnostic and Prescriptive Analytics
  • Iteration of previous concepts (e.g. Storyboard, Dashboarding)
  • Business Presentation Skills
  • Customer Segmentation (TBD)
  • Market Basket Analysis (TBD)
  • Competitive Positioning (TBD)
Natural Language Process: Analyzing Text Data from the Web
In many use cases, the most important information is written down in words and not conveniently tagged, making it difficult for computers to process and understand the content. In this sprint, we will build a web scraper to retrieve text data from the internet and apply Natural Language Process (NLP) techniques.

    KEY TOPICS
  • Use APIs and scraping tools such as Beautiful Soup to retrieve web data
  • Named Entity Recognition
  • Sentiment Analysis
  • Topic Modeling
The Company Business Review is the final project.

Graduation requirements

Graduation requirements differences between the Data Science Fellowship and the Data Analytics Bootcamp
Data Science Fellowship
Data Analytics Bootcamp
  • Complete 4 sprint outputs
  • Complete a capstone project
  • Present the capstone project during Demo Day
  • Complete 4 sprint outputs
  • Complete the final presentation

Qualifications

Qualifications differences between the Data Science Fellowship and the Data Analytics Bootcamp
Data Science Fellowship
Data Analytics Bootcamp
Entrance assessment:
    2 required parts
  • Multiple choice exam: On basic Python and Statistics. This first part is timed.
  • Essay portion: On your motivations for joining the Fellowship. This second part is untimed.
Qualifications:
  • Basic Python Knowledge: Before joining, you will need to be familiar with basic Python programming. This is the basis of the entrance assessment.
Entrance assessment:
    1 required exam
  • Multiple choice exam: On Excel knowledge, Business Insights, Critical Thinking, and Quantitative Reasoning. This is timed.
Qualifications:
  • Basic Excel Knowledge: You will need to know the fundamental formulas of Excel such as: Mean, Median, Mode, Max, Min, SUM, AVERAGE, and COUNT. You will also need to know how to create simple graphs on Excel.

What are the qualifications for both programs?

  • English: You need to be proficient in spoken and written English (B2 level, at a minimum).
  • Collaboration skills: You will spend a lot of time working with peers to mimic the work environment. We are looking for those who are ready to work in teams.
  • Growth mindset and grit: You will receive mentorship and feedback. So we are looking for those who have professionalism and the mindset to grow, as well as the grit to grind through the challenges of learning new skills.

Tuition fee and Payment methods

Tuition fee and Payment methods differences between the Data Science Fellowship and the Data Analytics Bootcamp
Data Science Fellowship
Data Analytics Bootcamp

Php 60, 000

Modes of Payment:
  • Payment:
    • Upfront Payment plan - Receive a 5% discount off of the total tuition when you choose to pay upfront. Final price of the Fellowship will be Php 57,000.

    • Installments Payment plan - We also provide students with the option to spread out the total tuition payment of Php 60,000 (USD1,200) over 3 months, paying only Php 20,000 (USD400) per month with 0% interest.
  • Study Now, Pay Later
  • Scholarships

Php 28, 000

Modes of Payment:
  • Payment:
    • Upfront Payment plan - Receive a 5% discount off of the total tuition when you choose to pay upfront. Final price of the Bootcamp will be Php 26,600.

    • Installments Payment plan - We also provide students with the option to spread out the total tuition payment of Php 28,000 (USD600) over 2 months, paying only Php 14,000 (USD300) per month with 0% interest.
    • Study Now, Pay Later
    • Scholarship

We will dive deeper into the Study Now, Pay Later feature and scholarships in the next tables.

Study Now, Pay Later feature

Study Now, Pay Later feature differences between the Data Science Fellowship and the Data Analytics Bootcamp
Data Science Fellowship
Data Analytics Bootcamp
Our loan providers (aka our financing partners):
  • Bukas
Our loan providers (aka our financing partners):
  • Bukas
  • InvestEd

Scholarships

Scholarships differences between the Data Science Fellowship and the Data Analytics Bootcamp
Data Science Fellowship
Data Analytics Bootcamp
Aral-Aral Scholarship
  • Covers full cost of tuition
  • Awarded on the basis of merit and need
  • Scholarship recipients may commit 2-3 hours per month to host online Aral-Aral Learning Circles within the free Eskwelabs Aral-Aral Community.
    Requires a Scholarship Interview

Data for Good Scholarship
  • Covers full cost of tuition
  • A competitive scholarship for incoming Fellows who pursue data science solutions for urgent social and environmental challenges.
  • Requires a Scholarship Interview
Pay-it-Forward Scholarship
  • Covers full cost of tuition
  • Awarded on the basis of merit and need
  • Scholarship recipients are asked to become ambassadors for Eskwelabs in virtual learning communities to promote and teach data literacy to others who may not be able to afford a formal data education.
  • Requires a Scholarship Interview

Job guarantee and Job interview guarantee features

What does the job interview guarantee mean? It means that our graduates will have guaranteed first interviews with our company partners.

What does the job guarantee mean? Students availing of this job guarantee feature who fail to secure employment or internship within a certain period after graduation will have their tuition refunded.

Job guarantee and Job interview guarantee features differences between the Data Science Fellowship and the Data Analytics Bootcamp
Data Science Fellowship
Data Analytics Bootcamp
Job Interview guarantee for graduates: Yes

Job guarantee period in contract: If the Data Science Fellowship Fellow availing of this job guarantee feature fails to secure employment or internship within nine (9) months of completion of the Data Science Fellowship, the tuition fee will be refunded.
Job Interview guarantee for graduates: Yes

Job guarantee period in contract: If the Data Analytics Bootcamp Analyst availing of this job guarantee feature fails to secure employment or internship within six (6) months of completion of the Data Analytics Bootcamp, the tuition fee will be refunded.


RECOMMENDED READING

  • If this is your first time reading about the Data Analytics Bootcamp, we recommend checking out the program in more detail here.
  • Ready to apply? Get started by signing up here. Cohort 4 of the Data Analytics Bootcamp starts on October 11, 2021; the admissions process is currently ongoing!

  • If this is your first time reading about the Data Science Fellowship, we recommend checking out the program in more detail here.
  • Ready to apply? Get started by signing up here. Cohort 8 of the Data Science Fellowship starts on September 6, 2021; the admissions process is currently ongoing!