Kickstart Your Career with  
  Northeastern’s Data Analytics Bootcamp  

Northeastern University D’Amore-McKim School of Business Career Accelerator Studio in Data Analytics

Data analytics is a high-growth field, with a promising, high-reward career path. The Northeastern University Career Accelerator Studio in Data Analytics is an ideal education program for someone who wants to make a career change and become a data analyst.

This certificate program offered through the university’s business school offers focused content and an experiential curriculum in introductory programming, math, statistics, machine learning and coding.

Participants earn “badges” (micro-credentials) for AWS, Salesforce, and Tableau – platforms widely used by companies for data analytics. The program also offers the opportunity to work on live projects, providing practical, real world experience to students.

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Length of Northeastern University’s Data Analytics Bootcamp?

The program is fully remote and online; consists of 26 modules (recommended pace: 1 module per week), split into 2 courses (101 & 201). Each module has specific learning objectives and corresponding success criteria.

 

  • Course 101 has 10 modules
  • Course 201 has 16 modules
  • Commitment of at least 10-12 hours per week
  • Must complete the entire course within 26 weeks
  • Regular walk-in sessions and bookable, individual support sessions are available

What Financing Options Are Available for Northeastern University’s Data Analytics Bootcamp?

The cost of this program is $17,000, which includes your non-refundable $500 enrollment fee payable upon acceptance of the admission offer.

Students may pay the tuition up-front or choose from financing options as outlined on the Northeastern University Financing Options page.

Many students have used an Income Share Agreement (ISA) to finance this program. Learn more about ISAs.

Northeastern University’s Data Analytics Bootcamp Curriculum and Schedule

Content:

This course introduces the Python programming language, its syntax, programming principles, mathematical functionality and suitability for practical data analysis. Learners will be given the tools to design and implement basic Python programs for data analytics applications.

Indicative topics include:

  • Introduction to Programming and Python
  • Control Structures
  • Functions
  • Structures

Content:

This course introduces the foundational mathematical and statistical knowledge and tools required for programming and data analytics. Learners will be given the tools and terminology to solve basic mathematical and statistical problems.

Indicative topics include:

  • Python Packages for Mathematical Techniques in Data Science
  • Principles of Proof and Hypothesis Testing
  • Linear Algebra
  • Hypothesis Testing

Content:

This course explores how analytics and predictive modeling generate business and develop policies. It introduces learners to business concepts, terminology and strategic frameworks for analyzing the external and internal business environments and developing digital transformation strategies.

Indicative topics include:

  • Digital Transformation in Business
  • Business Modeling
  • Business Data Analysis
  • Ethics

Content:

This course introduces the subject of data analytics. Learners will be taught how raw data is collected, stored, cleansed and interrogated in order to contribute to the needs of organizations. Learners will apply Python packages commonly used for data analytics, encompassing basic graphical, numerical and statistical tools. Learners will be given the tools to understand the issues with data and datasets and how to overcome them to ensure robust analyses.

Indicative topics include:

  • The Data Science Lifecycle
  • Data cleansing and manipulation, modeling and visualization
  • Cloud Analytics

Content:

This course develops learners’ knowledge and skills of data analytics, using more advanced techniques and thinking. In particular, learners will develop skills in data analysis, artificial intelligence, machine learning and reporting.

Indicative topics include:

  • Predictive Modelling for Analysts
  • Advanced Cloud Computing
  • Data Visualization, Reporting and Dashboards

Content:

A hands-on, mini data analytics project applying the data science lifecycle. Learners will identify a business problem and manipulate, analyze, model and visualize data using Python. The project aims to simulate a real-life business.

Where is Northeastern University’s Data Analytics Bootcamp Located?

This program is offered online only so it is entirely remote.

Requirements to attend are as follows:

  • Must have unlimited access to a personal computer / laptop.
  • Must have unlimited access to the internet.

Careers for Graduates of Northeastern University’s Data Analytics Bootcamp

Average U.S. Salary for a Data Analyst

 

    • $65,896: Current average annual salary in the US for an entry-level data analyst on Indeed
    • $74, 081: Current average annual salary in the US for an entry-level data analyst on Glassdoor
    •  
    • (Last updated: March 18, 2022)

Current U.S. Job Openings in Data Analytics

 

    • 47,355: Number of “Data Analyst” jobs currently listed on on Indeed –
      8,997 of which are Remote positions.
    • 24,922: Number of “Data Analyst” jobs currently listed on Glassdoor –
      5,023 of which are Remote positions.
    •  
    • (Last updated: March 23, 2022)

Find job openings through MentorWorks’ network of corporate partners:

Check for Current Data Analyst Job Openings

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