Course Name | Start Date | Rating | |
---|---|---|---|
|
How to Win a Data Science Competition: Learn from Top Kagglers
Coursera
5 weeks
5 weeks
|
||
|
openSAP
5 weeks, 4-6 hours a week
5 weeks, 4-6 hours a week
|
||
|
Data Analyst
edX
Professional Certificate
38 weeks, 2-4 hours a week
38 weeks, 2-4 hours a week
|
||
|
Probability - The Science of Uncertainty and Data
edX
16 weeks, 10-14 hours a week
16 weeks, 10-14 hours a week
|
||
|
Big Data Analysis with Apache Spark
edX
4 weeks, 5-10 hours a week
4 weeks, 5-10 hours a week
|
||
|
Machine Learning
Coursera
11 weeks, 61 hours a week
11 weeks, 61 hours a week
|
||
|
Mining Massive Datasets
edX
7 weeks, 5-10 hours a week
7 weeks, 5-10 hours a week
|
||
|
The Analytics Edge
edX
13 weeks, 10-15 hours a week
13 weeks, 10-15 hours a week
|
||
|
IBM Data Science
Coursera
Professional Certificate
48 weeks, 4 hours a week
48 weeks, 4 hours a week
|
||
|
IBM AI Engineering
Coursera
Professional Certificate
39 weeks, 3 hours a week
39 weeks, 3 hours a week
|
||
|
Udacity
Nanodegree
2 months 3 weeks 3 days
2 months 3 weeks 3 days
|
||
|
Natural Language Processing
Udacity
Nanodegree
2 months 2 weeks 6 days
2 months 2 weeks 6 days
|
||
|
Deep Learning
edX
Professional Certificate
26 weeks, 2-4 hours a week
26 weeks, 2-4 hours a week
|
||
|
IBM Data Science
edX
Professional Certificate
49 weeks, 3-5 hours a week
49 weeks, 3-5 hours a week
|
||
|
Applied AI
edX
Professional Certificate
21 weeks, 2-5 hours a week
21 weeks, 2-5 hours a week
|
||
|
Data Science
Coursera
Specialization
48 weeks, 7 hours a week
48 weeks, 7 hours a week
|
||
|
Computational Social Science
Coursera
Specialization
26 weeks, 3 hours a week
26 weeks, 3 hours a week
|
||
|
Advanced Data Science with IBM
Coursera
Specialization
17 weeks, 5 hours a week
17 weeks, 5 hours a week
|
||
|
IBM Applied AI
Coursera
Professional Certificate
26 weeks, 3 hours a week
26 weeks, 3 hours a week
|
||
|
Data Engineering Foundations
Coursera
Specialization
22 weeks, 5 hours a week
22 weeks, 5 hours a week
|
||
|
IBM Data Analyst
Coursera
Professional Certificate
48 weeks, 3 hours a week
48 weeks, 3 hours a week
|
||
|
IBM Machine Learning
Coursera
Professional Certificate
30 weeks, 3 hours a week
30 weeks, 3 hours a week
|
||
|
IBM Data Engineering
Coursera
Professional Certificate
65 weeks, 4 hours a week
65 weeks, 4 hours a week
|
||
|
Data Science:Â Productivity Tools
edX
8 weeks, 1-2 hours a week
8 weeks, 1-2 hours a week
|
||
|
Deep Learning with IBM
edX
Professional Certificate
31 weeks, 2-4 hours a week
31 weeks, 2-4 hours a week
|
||
|
Using Python to Access Web Data
Coursera
18 hours 45 minutes
18 hours 45 minutes
|
||
|
An Introduction to Interactive Programming in Python (Part 1)
Coursera
19 hours 18 minutes
19 hours 18 minutes
|
||
|
Computational Social Science Methods
Coursera
11 hours 20 minutes
11 hours 20 minutes
|
||
|
Data Mining Methods
Coursera
1 day 4 minutes
1 day 4 minutes
|
||
|
Fundamentals of Scalable Data Science
Coursera
1 day 3 hours 27 minutes
1 day 3 hours 27 minutes
|
||
|
Fundamentals of Reinforcement Learning
Coursera
15 hours 9 minutes
15 hours 9 minutes
|
||
|
Google Cloud Fundamentals: Core Infrastructure
Coursera
5 hours 59 minutes
5 hours 59 minutes
|
||
|
Google Cloud Big Data and Machine Learning Fundamentals
Coursera
9 hours 29 minutes
9 hours 29 minutes
|
||
|
Neural Networks and Deep Learning
Coursera
1 day 35 minutes
1 day 35 minutes
|
||
|
Practical Time Series Analysis
Coursera
1 day 1 hour 58 minutes
1 day 1 hour 58 minutes
|
||
|
Python Data Structures
Coursera
18 hours 50 minutes
18 hours 50 minutes
|
||
|
Social Network Analysis
Coursera
10 hours 10 minutes
10 hours 10 minutes
|
||
|
Intro to Analytic Thinking, Data Science, and Data Mining
Coursera
7 hours 15 minutes
7 hours 15 minutes
|
||
|
Programming for Everybody (Getting Started with Python)
Coursera
18 hours 45 minutes
18 hours 45 minutes
|
||
|
Elements of AI
Independent
6 weeks, 5-10 hours a week
6 weeks, 5-10 hours a week
|
Get personalized course recommendations, track subjects and courses with reminders, and more.