Course Information
Registration period
Year-round Recruitment
Course Level
Study Mode
Language
English
Taught by
Dr. Isaac Faber
Rating
Course Overview
A complete survey of all core skills required on the job
This is an ambitious course. The goal here is simple: Only teach what you need to know for day 1 of your first data science job. No fluff, nothing out of context, no topics that are not relevant to real world applications. We will cover EVERY core topic and tool required for those new to data science: Python, R, SQL, Useful Math/Stats/Algorithms, Tableau, and Excel in depth. The course will cover skills that align with three different job types:
- Data Analyst
- General Data Scientist
- Machine Learning Engineer
You can expect to learn from first principles the foundational topics and tools used in practice today. We will avoid topics that are not useful or are simply too advanced when starting out. Your journey will be guided by the Data Science Road Map, a collection of the best resources gathered through years of experience by the instructor.
In addition, we will survey every important technology required on the job including GitHub, Kaggle, the basics of cloud, web development and docker. With over 200 videos, readings, and assignments, you can be sure you will be well prepared to join the data community.
If you are just getting started or want to fill in some of your knowledge gaps this course is for you!
Course Content
- 10 section(s)
- 267 lecture(s)
- Section 1 Introduction - First Principals
- Section 2 Data Analyst - Case Study - Intro & Basic Spreadsheets
- Section 3 Data Analyst - Case Study - Intermediate Spreadsheets
- Section 4 Data Analyst - Case Study - Advanced Spreadsheets
- Section 5 Data Analyst - Case Study - SQL Basics
- Section 6 Data Analyst - Case Study - SQL Intermediate and Advanced
- Section 7 Data Analyst - Case Study - Business Intelligence and Tableau Introduction
- Section 8 Data Analyst - Case Study - Tableau Intermediate and Advanced Topics
- Section 9 Data Scientist - Case Study - Introduction to R
- Section 10 Data Scientist - Case Study - Exploratory Data Analysis and the R Tidyverse
What You’ll Learn
- Learn all necessary core skills for Data Analysis, Data Science, and Machine Learning
- Understand the first principles of data science and why it is so popular and important
- Learn how to use, from scratch, Python, R, SQL, Tableau, and MS Excel for data science
- Learn about a broad range of data science and machine learning libraries and resources
- Build and host a personal resume and portfolio of data science projects using GitHub Pages
- Learn about key supporting skills like Git/version-control, Kaggle, Databases, Command Line tools, and much more!
- Learn how to setup development environments from scratch in R and Python
- Learn about important related technologies like cloud, docker, and web development,
- Learn to deploy a machine learning model using docker
Skills covered in this course
Reviews
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DDonald McKinney
Love the course.
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CCemil Altay
English subtitles are very bad. Without this problem, very good Data Scientist courses. I like Isaac Faber expressions and examples. He's very understandable wording and readable coding.
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SSanthosh S
The course content was top-notch. It covered all the fundamental concepts of data science using Python, from data manipulation and visualization to machine learning. The explanations were clear, and the examples were practical, making it easy to grasp even for beginners like me.
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LLasya S
The course is providing a truly immersive and enlightening learning experience. The knowledgeable instructors, engaging content, and activities made it an valuable opportunity for personal and professional growth.
