Nanodegree Data Scientist.

Bootcamp AI

About This Course

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 prerequisites, Bootcamp AI has courses and programs that prepare you
for this Nanodegree program.

3 months program

Certificate

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.

Requirements

  • 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.

Curriculum

454 Lessons

Welcome to the Nanodegree program

Welcome to the Machine Learning Engineer Program & Projects
Program Structure
Skills that Set You Apart
Connecting with Your Community
Access the Career Portal
How Do I Find Time for My Nanodegree?00:00:00
Slack Community00:00:00

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

OOP

Portfolio Exercise: Upload a Package to PyPi

Part 15-Module 01-Lesson 06_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

Part 16-Module 01-Lesson 04_Machine Learning Pipelines

Part 16-Module 02-Lesson 01_Project Disaster Response Pipeline

Part 17-Module 02-Lesson 01_Concepts in Experiment Design

Part 17-Module 02-Lesson 02_Statistical Considerations in Testing

Part 17-Module 02-Lesson 03_AB Testing Case Study

Part 17-Module 02-Lesson 04_Portfolio Exercise Starbucks

Part 17-Module 03-Lesson 01_Introduction to Recommendation Engines

Part 17-Module 03-Lesson 02_Matrix Factorization for Recommendations

Part 17-Module 04-Lesson 01_Recommendation Engines

Part 17-Module 05-Lesson 01_Upcoming Lesson

Sentiment Prediction RNN

Convolutional Neural Networks

Transfer Learning

Weight Initialization

Autoencoders

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

Write a review

Group 1 (17)
Level
Intermediate
Lectures
454 lectures
Language
English Español

Pick a plan

Want to receive push notifications for all major on-site activities?

Wishlist 0
Open wishlist page Continue shopping