Machine Learning for Data Science and Analytics
Machine Learning is a growing field that is used when searching the web, placing ads, credit scoring, stock trading and for many other applications.
This data science course is an introduction to machine learning and algorithms. You will develop a basic understanding of the principles of machine learning and derive practical solutions using predictive analytics. We will also examine why algorithms play an essential role in Big Data analysis.
What you'll learn
- What machine learning is and how it is related to statistics and data analysis
- How machine learning uses computer algorithms to search for patterns in data
- How to use data patterns to make decisions and predictions with real-world examples from healthcare involving genomics and preterm birth
- How to uncover hidden themes in large collections of documents using topic modeling
- How to prepare data, deal with missing data and create custom data analysis solutions for different industries
- Basic and frequently used algorithmic techniques including sorting, searching, greedy algorithms and dynamic programming
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| Rating | 3.0★ based on 15 ratings |
|---|---|
| Length | 5 weeks |
| Effort | 5 weeks, 7–10 hours per week |
| Starts | On Demand (Start anytime) |
| Cost | $99 |
| From | Columbia University, ColumbiaX via edX |
| Instructors | Professor Ansaf Salleb-Aouissi, Cliff Stein, David Blei, Itsik Peer, Mihalis Yannakakis, Peter Orbanz, Ansaf Salleb-Aouissi |
| Download Videos | On all desktop and mobile devices |
| Language | English |
| Subjects | Business Programming Data Science |
| Tags | Business & Management Computer Science Data Analysis & Statistics Engineering |
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What people are saying
for this course
do not pay for
DO NOT PAY FOR THIS COURSE!!!
will get ripped off
YOU WILL GET RIPPED OFF!!!
bit bigger than expected
Although the proportion of algorithms is bit bigger than expected but the course does provide a good overview of the field.
its syllabus ran like
There's no clear objective for this course and its syllabus ran like an extended introduction to everything and anything we can think off.
stats work together which
It helped me understand ML little by little resolving lots of confusions about how ml and stats work together which were not removed in may other courses that I took online.
like an earlier reviewer
Like an earlier reviewer said, it is unclear who this course is meant to be for, and the outcome they aim to help learners achieve.
another one given
Of course you can expect some differences from a speaker to another one given the large number of speakers and the many covered topics, however, despite this, this course has worked for me.
expect some differences
scientist over night
It is of course not realistic to assume that it will make you a data scientist over night but it is a good platform to start with.
already familiar
The lectures are nice and the material is very interesting, but they assume you are already familiar with the material.
clear objective
Careers
An overview of related careers and their average salaries in the US. Bars indicate income percentile.
Research Scientist-Machine Learning $55k
Cloud Architect - Azure / Machine Learning $75k
Watson Machine Learning Engineer $81k
Machine Learning Software Developer $103k
Software Engineer (Machine Learning) $116k
Applied Scientist, Machine Learning $130k
Autonomy and Machine Learning Solutions Architect $131k
Applied Scientist - Machine Learning -... $136k
RESEARCH SCIENTIST (MACHINE LEARNING) $147k
Machine Learning Engineer 2 $161k
Machine Learning Scientist Manager $170k
Machine Learning Scientist, Personalization $213k
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| Rating | 3.0★ based on 15 ratings |
|---|---|
| Length | 5 weeks |
| Effort | 5 weeks, 7–10 hours per week |
| Starts | On Demand (Start anytime) |
| Cost | $99 |
| From | Columbia University, ColumbiaX via edX |
| Instructors | Professor Ansaf Salleb-Aouissi, Cliff Stein, David Blei, Itsik Peer, Mihalis Yannakakis, Peter Orbanz, Ansaf Salleb-Aouissi |
| Download Videos | On all desktop and mobile devices |
| Language | English |
| Subjects | Business Programming Data Science |
| Tags | Business & Management Computer Science Data Analysis & Statistics Engineering |
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