Data Scientist Specialization Bootcamp

Bootcamp AI

About This Course

3 months program

The Data Scientist Nanodegree program is an advanced program designed to prepare you for data scientist jobs. As such, you should have a high comfort level with a variety of topics before starting the program. In order to successfully complete this program, we strongly recommend that the following prerequisites are fulfilled. If you do not have the necessary  rerequisites, Bootcamp AI has courses and programs that prepare you for this Nanodegree program.


To share in LinkedIn

You can share your Certificates in the Certifications section of your LinkedIn profile, on your printed resume, or in other documents.



Learning Objectives

By the end of the program, you’ll have an impressive portfolio of real-world projects, and valuable hands-on experience. You’ll also receive career support via profile and portfolios reviews to help make sure you’re ready to establish a successful data science career, and land a job you love.


  • Python programming, including common data analysis libraries (NumPy, pandas, Matplotlib).
  • SQL programming
  • Statistics (Descriptive and Inferential)
  • Calculus
  • Linear Algebra
  • Experience wrangling and visualizing data

Target Audience

  • This program offers an ideal path for experienced programmers and data analysts to advance their data science careers. If you’re interested in deepening your expertise in the fields of analytics, machine learning, data engineering, and/or data science, this is a great way to get hands on practice with a variety of techniques and learn to build end to end data science solutions.


565 Lessons

Welcome to the Nanodegree program

01. Welcome00:00:00Preview
02. Meet the Instructors00:00:00
03. Term 2 Projects00:00:00
03.2 Term 2 Projects00:00:00
03.3 Term 2 Projects00:00:00
03.4 Term 2 Projects00:00:00
04. Program Structure & Syllabus
05. Learning Plan – First Two Weeks
06. How to Succeed00:00:00
Words of Encouragement00:00:00

The Skills That Set You Apart

The Data Science Process

Learn the data science process, including how to build effective data visualizations, and how to communicate with various stakeholders

Communicating to Stakeholders

Project Write A Data Science Blog Post

In this project, learners will choose a dataset, identify three questions, and analyze the data to find answers to these questions. They will create a GitHub repository with their project, and write a blog post to communicate their findings to the appropriate audience. This project will help learners reinforce and extend their knowledge of machine learning, data visualization, and communication.

Introduction to Software Engineering

In this lesson, you’ll write production-level code and practice object-oriented programming, which you can integrate into machine learning projects.

Software Engineering Practices Pt I

Software Engineering Practices Pt II


Portfolio Exercise: Upload a Package to PyPi

Web Development

Portfolio Exercise: Deploy a Data Dashboard

Introduction to Data Engineering

ETL Pipelines

Introduction to NLP

Learn Natural Language Processing one of the fields with the most real applications of Deep Learning

Machine Learning Pipelines

Disaster Response Pipeline

Project1: Disaster Response Pipeline

Concepts in Experiment Design

Statistical Considerations in Testing

Statistical Considerations in Testing

AB Testing Case Study

A/B Testing Case Study

Portfolio Exercise Starbucks

Introduction to Recommendation Engines

Matrix Factorization for Recommendations

Recommendation Engines

Upcoming Lesson

Sentiment Prediction RNN

Convolutional Neural Networks

Transfer Learning

Weight Initialization


Job Search

Find your dream job with continuous learning and constant effort

Refine Your Entry-Level Resume

Craft Your Cover Letter

Optimize Your GitHub Profile

Develop Your Personal Brand

Group 1 (17)
565 lectures
English Español

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