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update on intro

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mhjensen
2020-08-19 11:44:39 +02:00
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commit 918b257206
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doc/pub/Intro2Course/html/._Intro2Course-bs010.html
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@@ -44,26 +44,27 @@ Automatically generated HTML file from DocOnce source
'sections': [('Overview of first week', 2, None, '___sec0'),
('Lectures and ComputerLab', 2, None, '___sec1'),
('Course Format', 2, None, '___sec2'),
('Teachers and ComputerLab', 2, None, '___sec3'),
('Teachers', 2, None, '___sec3'),
('Deadlines for projects (tentative)', 2, None, '___sec4'),
('Learning outcomes', 2, None, '___sec5'),
('Prerequisites', 2, None, '___sec5'),
('Learning outcomes', 2, None, '___sec6'),
('Topics covered in this course: Statistical analysis and '
'optimization of data',
2,
None,
'___sec6'),
'___sec7'),
('Topics covered in this course: Machine Learning',
2,
None,
'___sec7'),
'___sec8'),
('Extremely useful tools, strongly recommended',
2,
None,
'___sec8'),
'___sec9'),
('Other courses on Data science and Machine Learning at UiO',
2,
None,
'___sec9')]}
'___sec10')]}
end of tocinfo -->
<body>
@@ -88,13 +89,14 @@ end of tocinfo -->
<!-- navigation toc: --> <li><a href="._Intro2Course-bs001.html#___sec0" style="font-size: 80%;">Overview of first week</a></li>
<!-- navigation toc: --> <li><a href="._Intro2Course-bs002.html#___sec1" style="font-size: 80%;">Lectures and ComputerLab</a></li>
<!-- navigation toc: --> <li><a href="._Intro2Course-bs003.html#___sec2" style="font-size: 80%;">Course Format</a></li>
<!-- navigation toc: --> <li><a href="._Intro2Course-bs004.html#___sec3" style="font-size: 80%;">Teachers and ComputerLab</a></li>
<!-- navigation toc: --> <li><a href="._Intro2Course-bs004.html#___sec3" style="font-size: 80%;">Teachers</a></li>
<!-- navigation toc: --> <li><a href="._Intro2Course-bs005.html#___sec4" style="font-size: 80%;">Deadlines for projects (tentative)</a></li>
<!-- navigation toc: --> <li><a href="._Intro2Course-bs006.html#___sec5" style="font-size: 80%;">Learning outcomes</a></li>
<!-- navigation toc: --> <li><a href="._Intro2Course-bs007.html#___sec6" style="font-size: 80%;">Topics covered in this course: Statistical analysis and optimization of data</a></li>
<!-- navigation toc: --> <li><a href="._Intro2Course-bs008.html#___sec7" style="font-size: 80%;">Topics covered in this course: Machine Learning</a></li>
<!-- navigation toc: --> <li><a href="._Intro2Course-bs009.html#___sec8" style="font-size: 80%;">Extremely useful tools, strongly recommended</a></li>
<!-- navigation toc: --> <li><a href="#___sec9" style="font-size: 80%;">Other courses on Data science and Machine Learning at UiO</a></li>
<!-- navigation toc: --> <li><a href="._Intro2Course-bs006.html#___sec5" style="font-size: 80%;">Prerequisites</a></li>
<!-- navigation toc: --> <li><a href="._Intro2Course-bs007.html#___sec6" style="font-size: 80%;">Learning outcomes</a></li>
<!-- navigation toc: --> <li><a href="._Intro2Course-bs008.html#___sec7" style="font-size: 80%;">Topics covered in this course: Statistical analysis and optimization of data</a></li>
<!-- navigation toc: --> <li><a href="._Intro2Course-bs009.html#___sec8" style="font-size: 80%;">Topics covered in this course: Machine Learning</a></li>
<!-- navigation toc: --> <li><a href="#___sec9" style="font-size: 80%;">Extremely useful tools, strongly recommended</a></li>
<!-- navigation toc: --> <li><a href="._Intro2Course-bs011.html#___sec10" style="font-size: 80%;">Other courses on Data science and Machine Learning at UiO</a></li>
</ul>
</li>
@@ -110,26 +112,22 @@ end of tocinfo -->
<a name="part0010"></a>
<!-- !split -->
<h2 id="___sec9" class="anchor">Other courses on Data science and Machine Learning at UiO </h2>
<h2 id="___sec9" class="anchor">Extremely useful tools, strongly recommended </h2>
<p>
The link here <a href="https://www.mn.uio.no/english/research/about/centre-focus/innovation/data-science/studies/" target="_self"><tt>https://www.mn.uio.no/english/research/about/centre-focus/innovation/data-science/studies/</tt></a> gives an excellent overview of courses on Machine learning at UiO.
<div class="panel panel-default">
<div class="panel-body">
<p> <!-- subsequent paragraphs come in larger fonts, so start with a paragraph -->
<ol>
<li> <a href="http://www.uio.no/studier/emner/matnat/math/STK2100/index-eng.html" target="_self">STK2100 Machine learning and statistical methods for prediction and classification</a>.</li>
<li> <a href="https://www.uio.no/studier/emner/matnat/ifi/IN3050/index-eng.html" target="_self">IN3050 Introduction to Artificial Intelligence and Machine Learning</a>. Introductory course in machine learning and AI with an algorithmic approach.</li>
<li> <a href="http://www.uio.no/studier/emner/matnat/math/STK-INF3000/index-eng.html" target="_self">STK-INF3000/4000 Selected Topics in Data Science</a>. The course provides insight into selected contemporary relevant topics within Data Science.</li>
<li> <a href="https://www.uio.no/studier/emner/matnat/ifi/IN4080/index.html" target="_self">IN4080 Natural Language Processing</a>. Probabilistic and machine learning techniques applied to natural language processing.</li>
<li> <a href="https://www.uio.no/studier/emner/matnat/math/STK-IN4300/index-eng.html" target="_self">STK-IN4300 Statistical learning methods in Data Science</a>. An advanced introduction to statistical and machine learning. For students with a good mathematics and statistics background.</li>
<li> <a href="http://www.uio.no/studier/emner/matnat/ifi/INF4490/" target="_self">INF4490 Biologically Inspired Computing</a>. An introduction to self-adapting methods also called artificial intelligence or machine learning.</li>
<li> <a href="https://www.uio.no/studier/emner/matnat/ifi/IN-STK5000/index-eng.html" target="_self">IN-STK5000 Adaptive Methods for Data-Based Decision Making</a>. Methods for adaptive collection and processing of data based on machine learning techniques.</li>
<li> <a href="https://www.uio.no/studier/emner/matnat/ifi/IN5400/" target="_self">IN5400/INF5860 Machine Learning for Image Analysis</a>. An introduction to deep learning with particular emphasis on applications within Image analysis, but useful for other application areas too.</li>
<li> <a href="https://www.uio.no/studier/emner/matnat/its/TEK5040/" target="_self">TEK5040 Deep learning for autonomous systems</a>. The course addresses advanced algorithms and architectures for deep learning with neural networks. The course provides an introduction to how deep-learning techniques can be used in the construction of key parts of advanced autonomous systems that exist in physical environments and cyber environments.</li>
<li> <a href="https://www.uio.no/studier/emner/matnat/math/STK4051/index-eng.html" target="_self">STK4051 Computational Statistics</a></li>
<li> <a href="https://www.uio.no/studier/emner/matnat/math/STK4021/index-eng.html" target="_self">STK4021 Applied Bayesian Analysis and Numerical Methods</a></li>
</ol>
<ul>
<li> GIT for version control, and GitHub or GitLab as repositories, highly recommended. This will be discussed during the first exercise session</li>
<li> Anaconda and other Python environments, see intro slides and first exercise session</li>
</ul>
</div>
</div>
<p>
<p>
<!-- navigation buttons at the bottom of the page -->
<ul class="pagination">
@@ -145,6 +143,8 @@ The link here <a href="https://www.mn.uio.no/english/research/about/centre-focus
<li><a href="._Intro2Course-bs008.html">9</a></li>
<li><a href="._Intro2Course-bs009.html">10</a></li>
<li class="active"><a href="._Intro2Course-bs010.html">11</a></li>
<li><a href="._Intro2Course-bs011.html">12</a></li>
<li><a href="._Intro2Course-bs011.html">&raquo;</a></li>
</ul>
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