-Basic knowledge in programming and mathematics, with an emphasis on -linear algebra. Knowledge of Python or/and C++ as programming -languages is strongly recommended and experience with Jupiter notebook -is recommended. Required courses are the equivalents to the University -of Oslo mathematics courses MAT1100, MAT1110, MAT1120 and at least one -of the corresponding computing and programming courses INF1000/INF1110 -or MAT-INF1100/MAT-INF1100L/BIOS1100/KJM-INF1100. Most universities -offer nowadays a basic programming course (often compulsory) where -Python is the recurring programming language. +
diff --git a/doc/pub/Intro2Course/html/._Intro2Course-bs007.html b/doc/pub/Intro2Course/html/._Intro2Course-bs007.html index 24443553c..4aabe5c46 100644 --- a/doc/pub/Intro2Course/html/._Intro2Course-bs007.html +++ b/doc/pub/Intro2Course/html/._Intro2Course-bs007.html @@ -46,25 +46,26 @@ Automatically generated HTML file from DocOnce source ('Course Format', 2, None, '___sec2'), ('Teachers', 2, None, '___sec3'), ('Deadlines for projects (tentative)', 2, None, '___sec4'), - ('Prerequisites', 2, None, '___sec5'), - ('Learning outcomes', 2, None, '___sec6'), + ('Recommended textbooks', 2, None, '___sec5'), + ('Prerequisites', 2, None, '___sec6'), + ('Learning outcomes', 2, None, '___sec7'), ('Topics covered in this course: Statistical analysis and ' 'optimization of data', 2, None, - '___sec7'), + '___sec8'), ('Topics covered in this course: Machine Learning', 2, None, - '___sec8'), + '___sec9'), ('Extremely useful tools, strongly recommended', 2, None, - '___sec9'), + '___sec10'), ('Other courses on Data science and Machine Learning at UiO', 2, None, - '___sec10')]} + '___sec11')]} end of tocinfo --> @@ -91,12 +92,13 @@ end of tocinfo -->
-
- -
-This course aims at giving you insights and knowledge about many of the central algorithms used in Data Analysis and Machine Learning. The course is project based and through various numerical projects, normally three, you will be exposed to fundamental research problems in these fields, with the aim to reproduce state of the art scientific results. Both supervised and unsupervised methods will be covered. The emphasis is on a frequentist approach, although we will try to link it with a Bayesian approach as well. You will learn to develop and structure large codes for studying different cases where Machine Learning is applied to, get acquainted with computing facilities and learn to handle large scientific projects. A good scientific and ethical conduct is emphasized throughout the course. More specifically, after this course you will - -
@@ -155,6 +144,7 @@ This course aims at giving you insights and knowledge about many of the central
-The course has two central parts - -
-The following topics will be covered +This course aims at giving you insights and knowledge about many of the central algorithms used in Data Analysis and Machine Learning. The course is project based and through various numerical projects, normally three, you will be exposed to fundamental research problems in these fields, with the aim to reproduce state of the art scientific results. Both supervised and unsupervised methods will be covered. The emphasis is on a frequentist approach, although we will try to link it with a Bayesian approach as well. You will learn to develop and structure large codes for studying different cases where Machine Learning is applied to, get acquainted with computing facilities and learn to handle large scientific projects. A good scientific and ethical conduct is emphasized throughout the course. More specifically, after this course you will
+The course has two central parts + +
+ +
The following topics will be covered
+The following topics will be covered
-The link here https://www.mn.uio.no/english/research/about/centre-focus/innovation/data-science/studies/ gives an excellent overview of courses on Machine learning at UiO. +
-
diff --git a/doc/pub/Intro2Course/html/Intro2Course-bs.html b/doc/pub/Intro2Course/html/Intro2Course-bs.html index c788d6e82..746e88c22 100644 --- a/doc/pub/Intro2Course/html/Intro2Course-bs.html +++ b/doc/pub/Intro2Course/html/Intro2Course-bs.html @@ -46,25 +46,26 @@ Automatically generated HTML file from DocOnce source ('Course Format', 2, None, '___sec2'), ('Teachers', 2, None, '___sec3'), ('Deadlines for projects (tentative)', 2, None, '___sec4'), - ('Prerequisites', 2, None, '___sec5'), - ('Learning outcomes', 2, None, '___sec6'), + ('Recommended textbooks', 2, None, '___sec5'), + ('Prerequisites', 2, None, '___sec6'), + ('Learning outcomes', 2, None, '___sec7'), ('Topics covered in this course: Statistical analysis and ' 'optimization of data', 2, None, - '___sec7'), + '___sec8'), ('Topics covered in this course: Machine Learning', 2, None, - '___sec8'), + '___sec9'), ('Extremely useful tools, strongly recommended', 2, None, - '___sec9'), + '___sec10'), ('Other courses on Data science and Machine Learning at UiO', 2, None, - '___sec10')]} + '___sec11')]} end of tocinfo --> @@ -91,12 +92,13 @@ end of tocinfo -->
Basic knowledge in programming and mathematics, with an emphasis on
@@ -286,7 +296,7 @@ Python is the recurring programming language.
The course has two central parts
@@ -344,7 +354,7 @@ The following topics will be covered
The link here https://www.mn.uio.no/english/research/about/centre-focus/innovation/data-science/studies/ gives an excellent overview of courses on Machine learning at UiO.
diff --git a/doc/pub/Intro2Course/html/Intro2Course-solarized.html b/doc/pub/Intro2Course/html/Intro2Course-solarized.html
index bfa55ec6f..9fd3cacc8 100644
--- a/doc/pub/Intro2Course/html/Intro2Course-solarized.html
+++ b/doc/pub/Intro2Course/html/Intro2Course-solarized.html
@@ -66,25 +66,26 @@ div { text-align: justify; text-justify: inter-word; }
('Course Format', 2, None, '___sec2'),
('Teachers', 2, None, '___sec3'),
('Deadlines for projects (tentative)', 2, None, '___sec4'),
- ('Prerequisites', 2, None, '___sec5'),
- ('Learning outcomes', 2, None, '___sec6'),
+ ('Recommended textbooks', 2, None, '___sec5'),
+ ('Prerequisites', 2, None, '___sec6'),
+ ('Learning outcomes', 2, None, '___sec7'),
('Topics covered in this course: Statistical analysis and '
'optimization of data',
2,
None,
- '___sec7'),
+ '___sec8'),
('Topics covered in this course: Machine Learning',
2,
None,
- '___sec8'),
+ '___sec9'),
('Extremely useful tools, strongly recommended',
2,
None,
- '___sec9'),
+ '___sec10'),
('Other courses on Data science and Machine Learning at UiO',
2,
None,
- '___sec10')]}
+ '___sec11')]}
end of tocinfo -->
Basic knowledge in programming and mathematics, with an emphasis on
@@ -255,7 +265,7 @@ Python is the recurring programming language.
The course has two central parts
@@ -318,7 +328,7 @@ The following topics will be covered
The link here https://www.mn.uio.no/english/research/about/centre-focus/innovation/data-science/studies/ gives an excellent overview of courses on Machine learning at UiO.
diff --git a/doc/pub/Intro2Course/html/Intro2Course.html b/doc/pub/Intro2Course/html/Intro2Course.html
index 6d15f0615..4744717ef 100644
--- a/doc/pub/Intro2Course/html/Intro2Course.html
+++ b/doc/pub/Intro2Course/html/Intro2Course.html
@@ -71,25 +71,26 @@ div { text-align: justify; text-justify: inter-word; }
('Course Format', 2, None, '___sec2'),
('Teachers', 2, None, '___sec3'),
('Deadlines for projects (tentative)', 2, None, '___sec4'),
- ('Prerequisites', 2, None, '___sec5'),
- ('Learning outcomes', 2, None, '___sec6'),
+ ('Recommended textbooks', 2, None, '___sec5'),
+ ('Prerequisites', 2, None, '___sec6'),
+ ('Learning outcomes', 2, None, '___sec7'),
('Topics covered in this course: Statistical analysis and '
'optimization of data',
2,
None,
- '___sec7'),
+ '___sec8'),
('Topics covered in this course: Machine Learning',
2,
None,
- '___sec8'),
+ '___sec9'),
('Extremely useful tools, strongly recommended',
2,
None,
- '___sec9'),
+ '___sec10'),
('Other courses on Data science and Machine Learning at UiO',
2,
None,
- '___sec10')]}
+ '___sec11')]}
end of tocinfo -->
Basic knowledge in programming and mathematics, with an emphasis on
@@ -260,7 +270,7 @@ Python is the recurring programming language.
The course has two central parts
@@ -323,7 +333,7 @@ The following topics will be covered
The link here https://www.mn.uio.no/english/research/about/centre-focus/innovation/data-science/studies/ gives an excellent overview of courses on Machine learning at UiO.
diff --git a/doc/pub/Intro2Course/ipynb/ipynb-Intro2Course-src.tar.gz b/doc/pub/Intro2Course/ipynb/ipynb-Intro2Course-src.tar.gz
index d97b0bbc2..0f091ddb5 100644
Binary files a/doc/pub/Intro2Course/ipynb/ipynb-Intro2Course-src.tar.gz and b/doc/pub/Intro2Course/ipynb/ipynb-Intro2Course-src.tar.gz differ
diff --git a/doc/pub/Intro2Course/pdf/Intro2Course-minted.pdf b/doc/pub/Intro2Course/pdf/Intro2Course-minted.pdf
index 5449dbdbd..b53b618c5 100644
Binary files a/doc/pub/Intro2Course/pdf/Intro2Course-minted.pdf and b/doc/pub/Intro2Course/pdf/Intro2Course-minted.pdf differ
diff --git a/doc/src/Intro2Course/Intro2Course.do.txt b/doc/src/Intro2Course/Intro2Course.do.txt
index 43e57cca1..4ffc0b8f0 100644
--- a/doc/src/Intro2Course/Intro2Course.do.txt
+++ b/doc/src/Intro2Course/Intro2Course.do.txt
@@ -81,7 +81,11 @@ Projects are handed in using _Canvas_. We use Github as repository for codes, be
!eblock
+!split
+===== Recommended textbooks =====
+* "Trevor Hastie, Robert Tibshirani, Jerome H. Friedman, The Elements of Statistical Learning, Springer":"https://www.springer.com/gp/book/9780387848570"
+* "Aurelien Geron, Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow, 2nd Edition":"https://www.oreilly.com/library/view/hands-on-machine-learning/9781492032632/"
!split
===== Prerequisites =====
Learning outcomes
+Learning outcomes
Topics covered in this course: Statistical analysis and optimization of data
+Topics covered in this course: Statistical analysis and optimization of data
Topics covered in this course: Machine Learning
+Topics covered in this course: Machine Learning
Extremely useful tools, strongly recommended
+Extremely useful tools, strongly recommended
Other courses on Data science and Machine Learning at UiO
+Other courses on Data science and Machine Learning at UiO
-Prerequisites
+Recommended textbooks
+
+
+
+
+
+
+Prerequisites
-Learning outcomes
+Learning outcomes
-Topics covered in this course: Statistical analysis and optimization of data
+Topics covered in this course: Statistical analysis and optimization of data
-Topics covered in this course: Machine Learning
+Topics covered in this course: Machine Learning
-Extremely useful tools, strongly recommended
+Extremely useful tools, strongly recommended
-Other courses on Data science and Machine Learning at UiO
+Other courses on Data science and Machine Learning at UiO
-Prerequisites
+Recommended textbooks
+
+
+
+
+
+
+Prerequisites
-Learning outcomes
+Learning outcomes
-Topics covered in this course: Statistical analysis and optimization of data
+Topics covered in this course: Statistical analysis and optimization of data
-Topics covered in this course: Machine Learning
+Topics covered in this course: Machine Learning
-Extremely useful tools, strongly recommended
+Extremely useful tools, strongly recommended
-Other courses on Data science and Machine Learning at UiO
+Other courses on Data science and Machine Learning at UiO