Level
Advanced
Prerequisites
Comfortable wrangling and analyzing data in Python; intermediate knowledge of Numpy and Pandas. Intermediate SQL. Inferential statistics, calculus, and data visualization
Course Duration
4 months
Udacity current price ( USD)
1356
Career Focus
This is a career-focused program meant to prepare you for a data science or data analyst role. Obtaining the skills required to be a Data Scientist will make you extremely valuable across many industries, and in many roles. Data Scientists work as Analysts, Statisticians, Engineers, and more. Some become Data and Analytics Managers, while others specialize as Database Administrators. As a graduate of this program, you’ll be prepared to seek out roles that run the gamut from generalist to specialist, and all points in between.
Target Audience
Students who want to enter the field of data science and already have a foundation in Calculus, stats, and Python programming. Developers who want to learn both machine learning and how to solve applied, practical data science problems. Students who want to focus on machine learning and learn a wider range of ML topics should look at the Machine Learning Engineer Nanodegree.
General Curriculum)
Machine Learning methods including supervised and unsupervised methods, and deep learning. Software Engineering focused on data science applications; Data Engineering focused on pipelines and deployment of models. Scaling to big data methods with Spark is optional content. Applications in recommendation systems. Writing to communicate about your results is emphasized.
Skill Covered
N/A
Tools
What They Need: Computer that can install/run the below programs
What They Will Learn/Use: Python, Jupyter Notebooks, Pandas, Numpy, SQL, FigureEight, Flask, scikit-learn (Python Library)
Projects
• Write a Data Science Blog Post
• Build Disaster Response Pipelines with FigureEight
• Design a Recommendation Engine with IBM
• Capstone – Build your own data science project. You will define the problem, identify and explore the data, perform your analyses, and present your solution in a blog post or frontend application.
Syllabus
Resources (blog posts, other)
Course Features
- Lectures 0
- Quizzes 0
- Duration 5 months
- Skill level All levels
- Students 0
- Assessments Yes