diff --git a/doc/pub/summary/html/._summary-bs000.html b/doc/pub/summary/html/._summary-bs000.html index 756a06171..44d322a14 100644 --- a/doc/pub/summary/html/._summary-bs000.html +++ b/doc/pub/summary/html/._summary-bs000.html @@ -59,11 +59,12 @@ Automatically generated HTML file from DocOnce source 2, None, '___sec6'), + ('Additional courses of interest', 2, None, '___sec7'), ('Best wishes to you all and thanks so much for your heroic ' 'efforts this semester', 2, None, - '___sec7')]} + '___sec8')]} end of tocinfo --> @@ -92,7 +93,8 @@ end of tocinfo -->
  • Machine learning
  • Learning outcomes and overarching aims of this course
  • Other courses on Data science and Machine Learning at UiO
  • -
  • Best wishes to you all and thanks so much for your heroic efforts this semester
  • +
  • Additional courses of interest
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  • Best wishes to you all and thanks so much for your heroic efforts this semester
  • @@ -149,6 +151,7 @@ end of tocinfo -->
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  • Machine learning
  • Learning outcomes and overarching aims of this course
  • Other courses on Data science and Machine Learning at UiO
  • -
  • Best wishes to you all and thanks so much for your heroic efforts this semester
  • +
  • Additional courses of interest
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  • Best wishes to you all and thanks so much for your heroic efforts this semester
  • @@ -126,6 +128,7 @@ end of tocinfo -->
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  • Machine learning
  • Learning outcomes and overarching aims of this course
  • Other courses on Data science and Machine Learning at UiO
  • -
  • Best wishes to you all and thanks so much for your heroic efforts this semester
  • +
  • Additional courses of interest
  • +
  • Best wishes to you all and thanks so much for your heroic efforts this semester
  • @@ -131,6 +133,7 @@ Does that match the experiences you have made this semester?
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  • diff --git a/doc/pub/summary/html/._summary-bs003.html b/doc/pub/summary/html/._summary-bs003.html index 63988a0d9..5d47ea732 100644 --- a/doc/pub/summary/html/._summary-bs003.html +++ b/doc/pub/summary/html/._summary-bs003.html @@ -59,11 +59,12 @@ Automatically generated HTML file from DocOnce source 2, None, '___sec6'), + ('Additional courses of interest', 2, None, '___sec7'), ('Best wishes to you all and thanks so much for your heroic ' 'efforts this semester', 2, None, - '___sec7')]} + '___sec8')]} end of tocinfo --> @@ -92,7 +93,8 @@ end of tocinfo -->
  • Machine learning
  • Learning outcomes and overarching aims of this course
  • Other courses on Data science and Machine Learning at UiO
  • -
  • Best wishes to you all and thanks so much for your heroic efforts this semester
  • +
  • Additional courses of interest
  • +
  • Best wishes to you all and thanks so much for your heroic efforts this semester
  • @@ -131,6 +133,7 @@ The course has two central parts
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  • diff --git a/doc/pub/summary/html/._summary-bs004.html b/doc/pub/summary/html/._summary-bs004.html index 23ac8d38b..e51a4d6aa 100644 --- a/doc/pub/summary/html/._summary-bs004.html +++ b/doc/pub/summary/html/._summary-bs004.html @@ -59,11 +59,12 @@ Automatically generated HTML file from DocOnce source 2, None, '___sec6'), + ('Additional courses of interest', 2, None, '___sec7'), ('Best wishes to you all and thanks so much for your heroic ' 'efforts this semester', 2, None, - '___sec7')]} + '___sec8')]} end of tocinfo --> @@ -92,7 +93,8 @@ end of tocinfo -->
  • Machine learning
  • Learning outcomes and overarching aims of this course
  • Other courses on Data science and Machine Learning at UiO
  • -
  • Best wishes to you all and thanks so much for your heroic efforts this semester
  • +
  • Additional courses of interest
  • +
  • Best wishes to you all and thanks so much for your heroic efforts this semester
  • @@ -138,6 +140,7 @@ The following topics will be covered
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  • diff --git a/doc/pub/summary/html/._summary-bs005.html b/doc/pub/summary/html/._summary-bs005.html index be0e9c6d2..d7b1abb48 100644 --- a/doc/pub/summary/html/._summary-bs005.html +++ b/doc/pub/summary/html/._summary-bs005.html @@ -59,11 +59,12 @@ Automatically generated HTML file from DocOnce source 2, None, '___sec6'), + ('Additional courses of interest', 2, None, '___sec7'), ('Best wishes to you all and thanks so much for your heroic ' 'efforts this semester', 2, None, - '___sec7')]} + '___sec8')]} end of tocinfo --> @@ -92,7 +93,8 @@ end of tocinfo -->
  • Machine learning
  • Learning outcomes and overarching aims of this course
  • Other courses on Data science and Machine Learning at UiO
  • -
  • Best wishes to you all and thanks so much for your heroic efforts this semester
  • +
  • Additional courses of interest
  • +
  • Best wishes to you all and thanks so much for your heroic efforts this semester
  • @@ -113,18 +115,13 @@ end of tocinfo -->

    The following topics will be covered -

    -
    %s
    - Linear methods for regression and classification; -
    %s
    - Boltzmann machines; -
    %s
    - Neural networks; -
    %s
    - Decisions trees and nearest neighbor algorithms -
    %s
    - Support vector machines -
    +
      +
    1. Linear methods for regression and classification;
    2. +
    3. Boltzmann machines;
    4. +
    5. Neural networks;
    6. +
    7. Decisions trees and nearest neighbor algorithms
    8. +
    9. Support vector machines
    10. +

    @@ -139,6 +136,7 @@ The following topics will be covered

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  • diff --git a/doc/pub/summary/html/._summary-bs006.html b/doc/pub/summary/html/._summary-bs006.html index a2ccdf4e5..e54d14306 100644 --- a/doc/pub/summary/html/._summary-bs006.html +++ b/doc/pub/summary/html/._summary-bs006.html @@ -59,11 +59,12 @@ Automatically generated HTML file from DocOnce source 2, None, '___sec6'), + ('Additional courses of interest', 2, None, '___sec7'), ('Best wishes to you all and thanks so much for your heroic ' 'efforts this semester', 2, None, - '___sec7')]} + '___sec8')]} end of tocinfo --> @@ -92,7 +93,8 @@ end of tocinfo -->
  • Machine learning
  • Learning outcomes and overarching aims of this course
  • Other courses on Data science and Machine Learning at UiO
  • -
  • Best wishes to you all and thanks so much for your heroic efforts this semester
  • +
  • Additional courses of interest
  • +
  • Best wishes to you all and thanks so much for your heroic efforts this semester
  • @@ -144,6 +146,7 @@ ethical conduct is emphasized throughout the course.
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  • diff --git a/doc/pub/summary/html/._summary-bs007.html b/doc/pub/summary/html/._summary-bs007.html index 301e16bf3..f64d65cbd 100644 --- a/doc/pub/summary/html/._summary-bs007.html +++ b/doc/pub/summary/html/._summary-bs007.html @@ -59,11 +59,12 @@ Automatically generated HTML file from DocOnce source 2, None, '___sec6'), + ('Additional courses of interest', 2, None, '___sec7'), ('Best wishes to you all and thanks so much for your heroic ' 'efforts this semester', 2, None, - '___sec7')]} + '___sec8')]} end of tocinfo --> @@ -92,7 +93,8 @@ end of tocinfo -->
  • Machine learning
  • Learning outcomes and overarching aims of this course
  • Other courses on Data science and Machine Learning at UiO
  • -
  • Best wishes to you all and thanks so much for your heroic efforts this semester
  • +
  • Additional courses of interest
  • +
  • Best wishes to you all and thanks so much for your heroic efforts this semester
  • @@ -116,7 +118,7 @@ The link here STK2100 Machine learning and statistical methods for prediction and classification.
  • IN3050 Introduction to Artificial Intelligence and Machine Learning. Introductory course in machine learning and AI with an algorithmic approach.
  • -
  • "STK-INF3000/4000 Selected Topics in Data Science:"http://www.uio.no/studier/emner/matnat/math/STK-INF3000/index-eng.html". The course provides insight into selected contemporary relevant topics within Data Science.
  • +
  • STK-INF3000/4000 Selected Topics in Data Science. The course provides insight into selected contemporary relevant topics within Data Science.
  • IN4080 Natural Language Processing. Probabilistic and machine learning techniques applied to natural language processing.
  • STK-IN4300 – Statistical learning methods in Data Science. An advanced introduction to statistical and machine learning. For students with a good mathematics and statistics background.
  • INF4490 Biologically Inspired Computing. An introduction to self-adapting methods also called artificial intelligence or machine learning.
  • @@ -138,6 +140,7 @@ The link here 7
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  • diff --git a/doc/pub/summary/html/._summary-bs008.html b/doc/pub/summary/html/._summary-bs008.html index 2f703b5b1..7f034f170 100644 --- a/doc/pub/summary/html/._summary-bs008.html +++ b/doc/pub/summary/html/._summary-bs008.html @@ -59,11 +59,12 @@ Automatically generated HTML file from DocOnce source 2, None, '___sec6'), + ('Additional courses of interest', 2, None, '___sec7'), ('Best wishes to you all and thanks so much for your heroic ' 'efforts this semester', 2, None, - '___sec7')]} + '___sec8')]} end of tocinfo --> @@ -92,7 +93,8 @@ end of tocinfo -->
  • Machine learning
  • Learning outcomes and overarching aims of this course
  • Other courses on Data science and Machine Learning at UiO
  • -
  • Best wishes to you all and thanks so much for your heroic efforts this semester
  • +
  • Additional courses of interest
  • +
  • Best wishes to you all and thanks so much for your heroic efforts this semester
  • @@ -108,12 +110,12 @@ end of tocinfo --> -

    Best wishes to you all and thanks so much for your heroic efforts this semester

    +

    Additional courses of interest

    -

    -



    - -

    +

      +
    1. STK4051 Computational Statistics
    2. +
    3. STK4021 Applied Bayesian Analysis and Numerical Methods
    4. +

    @@ -128,6 +130,8 @@ end of tocinfo -->

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  • diff --git a/doc/pub/summary/html/._summary-bs009.html b/doc/pub/summary/html/._summary-bs009.html new file mode 100644 index 000000000..f1ebcf1c3 --- /dev/null +++ b/doc/pub/summary/html/._summary-bs009.html @@ -0,0 +1,157 @@ + + + + + + + +Summary of course + + + + + + + + + + + + + + + + + + + +
    + +

     

     

     

    + + + + +

    Best wishes to you all and thanks so much for your heroic efforts this semester

    + +

    +



    + +

    + +

    + +

    + + +
    + + + + + + + +
    + +
    + + + + + + diff --git a/doc/pub/summary/html/summary-bs.html b/doc/pub/summary/html/summary-bs.html index 756a06171..44d322a14 100644 --- a/doc/pub/summary/html/summary-bs.html +++ b/doc/pub/summary/html/summary-bs.html @@ -59,11 +59,12 @@ Automatically generated HTML file from DocOnce source 2, None, '___sec6'), + ('Additional courses of interest', 2, None, '___sec7'), ('Best wishes to you all and thanks so much for your heroic ' 'efforts this semester', 2, None, - '___sec7')]} + '___sec8')]} end of tocinfo --> @@ -92,7 +93,8 @@ end of tocinfo -->
  • Machine learning
  • Learning outcomes and overarching aims of this course
  • Other courses on Data science and Machine Learning at UiO
  • -
  • Best wishes to you all and thanks so much for your heroic efforts this semester
  • +
  • Additional courses of interest
  • +
  • Best wishes to you all and thanks so much for your heroic efforts this semester
  • @@ -149,6 +151,7 @@ end of tocinfo -->
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  • diff --git a/doc/pub/summary/html/summary-reveal.html b/doc/pub/summary/html/summary-reveal.html index f9f575baf..fbdcd462c 100644 --- a/doc/pub/summary/html/summary-reveal.html +++ b/doc/pub/summary/html/summary-reveal.html @@ -200,18 +200,13 @@ The following topics will be covered

    The following topics will be covered -

    -
    %s
    - Linear methods for regression and classification; -
    %s
    - Boltzmann machines; -
    %s
    - Neural networks; -
    %s
    - Decisions trees and nearest neighbor algorithms -
    %s
    - Support vector machines -
    +
      +

    1. Linear methods for regression and classification;
    2. +

    3. Boltzmann machines;
    4. +

    5. Neural networks;
    6. +

    7. Decisions trees and nearest neighbor algorithms
    8. +

    9. Support vector machines
    10. +
    @@ -250,7 +245,7 @@ The link here STK2100 Machine learning and statistical methods for prediction and classification.

  • IN3050 Introduction to Artificial Intelligence and Machine Learning. Introductory course in machine learning and AI with an algorithmic approach.
  • -

  • "STK-INF3000/4000 Selected Topics in Data Science:"http://www.uio.no/studier/emner/matnat/math/STK-INF3000/index-eng.html". The course provides insight into selected contemporary relevant topics within Data Science.
  • +

  • STK-INF3000/4000 Selected Topics in Data Science. The course provides insight into selected contemporary relevant topics within Data Science.
  • IN4080 Natural Language Processing. Probabilistic and machine learning techniques applied to natural language processing.
  • STK-IN4300 – Statistical learning methods in Data Science. An advanced introduction to statistical and machine learning. For students with a good mathematics and statistics background.
  • INF4490 Biologically Inspired Computing. An introduction to self-adapting methods also called artificial intelligence or machine learning.
  • @@ -262,7 +257,17 @@ The link here Best wishes to you all and thanks so much for your heroic efforts this semester +

    Additional courses of interest

    + +
      +

    1. STK4051 Computational Statistics
    2. +

    3. STK4021 Applied Bayesian Analysis and Numerical Methods
    4. +
    + + + +
    +

    Best wishes to you all and thanks so much for your heroic efforts this semester





    diff --git a/doc/pub/summary/html/summary-solarized.html b/doc/pub/summary/html/summary-solarized.html index ac1894905..07d21aa85 100644 --- a/doc/pub/summary/html/summary-solarized.html +++ b/doc/pub/summary/html/summary-solarized.html @@ -53,11 +53,12 @@ div { text-align: justify; text-justify: inter-word; } 2, None, '___sec6'), + ('Additional courses of interest', 2, None, '___sec7'), ('Best wishes to you all and thanks so much for your heroic ' 'efforts this semester', 2, None, - '___sec7')]} + '___sec8')]} end of tocinfo --> @@ -143,18 +144,13 @@ The following topics will be covered

    The following topics will be covered -

    -
    %s
    - Linear methods for regression and classification; -
    %s
    - Boltzmann machines; -
    %s
    - Neural networks; -
    %s
    - Decisions trees and nearest neighbor algorithms -
    %s
    - Support vector machines -
    +
      +
    1. Linear methods for regression and classification;
    2. +
    3. Boltzmann machines;
    4. +
    5. Neural networks;
    6. +
    7. Decisions trees and nearest neighbor algorithms
    8. +
    9. Support vector machines
    10. +










    @@ -191,7 +187,7 @@ The link here STK2100 Machine learning and statistical methods for prediction and classification.
  • IN3050 Introduction to Artificial Intelligence and Machine Learning. Introductory course in machine learning and AI with an algorithmic approach.
  • -
  • "STK-INF3000/4000 Selected Topics in Data Science:"http://www.uio.no/studier/emner/matnat/math/STK-INF3000/index-eng.html". The course provides insight into selected contemporary relevant topics within Data Science.
  • +
  • STK-INF3000/4000 Selected Topics in Data Science. The course provides insight into selected contemporary relevant topics within Data Science.
  • IN4080 Natural Language Processing. Probabilistic and machine learning techniques applied to natural language processing.
  • STK-IN4300 – Statistical learning methods in Data Science. An advanced introduction to statistical and machine learning. For students with a good mathematics and statistics background.
  • INF4490 Biologically Inspired Computing. An introduction to self-adapting methods also called artificial intelligence or machine learning.
  • @@ -202,7 +198,16 @@ The link here Best wishes to you all and thanks so much for your heroic efforts this semester +

    Additional courses of interest

    + +
      +
    1. STK4051 Computational Statistics
    2. +
    3. STK4021 Applied Bayesian Analysis and Numerical Methods
    4. +
    + +









    + +

    Best wishes to you all and thanks so much for your heroic efforts this semester





    diff --git a/doc/pub/summary/html/summary.html b/doc/pub/summary/html/summary.html index 0b5071d6a..6063bafdc 100644 --- a/doc/pub/summary/html/summary.html +++ b/doc/pub/summary/html/summary.html @@ -58,11 +58,12 @@ div { text-align: justify; text-justify: inter-word; } 2, None, '___sec6'), + ('Additional courses of interest', 2, None, '___sec7'), ('Best wishes to you all and thanks so much for your heroic ' 'efforts this semester', 2, None, - '___sec7')]} + '___sec8')]} end of tocinfo --> @@ -148,18 +149,13 @@ The following topics will be covered

    The following topics will be covered -

    -
    %s
    - Linear methods for regression and classification; -
    %s
    - Boltzmann machines; -
    %s
    - Neural networks; -
    %s
    - Decisions trees and nearest neighbor algorithms -
    %s
    - Support vector machines -
    +
      +
    1. Linear methods for regression and classification;
    2. +
    3. Boltzmann machines;
    4. +
    5. Neural networks;
    6. +
    7. Decisions trees and nearest neighbor algorithms
    8. +
    9. Support vector machines
    10. +










    @@ -196,7 +192,7 @@ The link here STK2100 Machine learning and statistical methods for prediction and classification.
  • IN3050 Introduction to Artificial Intelligence and Machine Learning. Introductory course in machine learning and AI with an algorithmic approach.
  • -
  • "STK-INF3000/4000 Selected Topics in Data Science:"http://www.uio.no/studier/emner/matnat/math/STK-INF3000/index-eng.html". The course provides insight into selected contemporary relevant topics within Data Science.
  • +
  • STK-INF3000/4000 Selected Topics in Data Science. The course provides insight into selected contemporary relevant topics within Data Science.
  • IN4080 Natural Language Processing. Probabilistic and machine learning techniques applied to natural language processing.
  • STK-IN4300 – Statistical learning methods in Data Science. An advanced introduction to statistical and machine learning. For students with a good mathematics and statistics background.
  • INF4490 Biologically Inspired Computing. An introduction to self-adapting methods also called artificial intelligence or machine learning.
  • @@ -207,7 +203,16 @@ The link here Best wishes to you all and thanks so much for your heroic efforts this semester +

    Additional courses of interest

    + +
      +
    1. STK4051 Computational Statistics
    2. +
    3. STK4021 Applied Bayesian Analysis and Numerical Methods
    4. +
    + +









    + +

    Best wishes to you all and thanks so much for your heroic efforts this semester





    diff --git a/doc/pub/summary/ipynb/ipynb-summary-src.tar.gz b/doc/pub/summary/ipynb/ipynb-summary-src.tar.gz index 8838b7403..98c43552a 100644 Binary files a/doc/pub/summary/ipynb/ipynb-summary-src.tar.gz and b/doc/pub/summary/ipynb/ipynb-summary-src.tar.gz differ diff --git a/doc/pub/summary/ipynb/summary.ipynb b/doc/pub/summary/ipynb/summary.ipynb index eb2a8a269..3447188df 100644 --- a/doc/pub/summary/ipynb/summary.ipynb +++ b/doc/pub/summary/ipynb/summary.ipynb @@ -83,25 +83,15 @@ "## Machine learning\n", "\n", "The following topics will be covered\n", - "%s\n", - " : \n", - " Linear methods for regression and classification;\n", + "1. Linear methods for regression and classification;\n", "\n", - "%s\n", - " : \n", - " Boltzmann machines;\n", + "2. Boltzmann machines;\n", "\n", - "%s\n", - " : \n", - " Neural networks;\n", + "3. Neural networks;\n", "\n", - "%s\n", - " : \n", - " Decisions trees and nearest neighbor algorithms\n", + "4. Decisions trees and nearest neighbor algorithms\n", "\n", - "%s\n", - " : \n", - " Support vector machines\n", + "5. Support vector machines\n", "\n", "## Learning outcomes and overarching aims of this course\n", "\n", @@ -137,7 +127,7 @@ "\n", "2. [IN3050 Introduction to Artificial Intelligence and Machine Learning](https://www.uio.no/studier/emner/matnat/ifi/IN3050/index-eng.html). Introductory course in machine learning and AI with an algorithmic approach. \n", "\n", - "3. \"STK-INF3000/4000 Selected Topics in Data Science:\"http://www.uio.no/studier/emner/matnat/math/STK-INF3000/index-eng.html\". The course provides insight into selected contemporary relevant topics within Data Science. \n", + "3. [STK-INF3000/4000 Selected Topics in Data Science](http://www.uio.no/studier/emner/matnat/math/STK-INF3000/index-eng.html). The course provides insight into selected contemporary relevant topics within Data Science. \n", "\n", "4. [IN4080 Natural Language Processing](https://www.uio.no/studier/emner/matnat/ifi/IN4080/index.html). Probabilistic and machine learning techniques applied to natural language processing. \n", "\n", @@ -151,6 +141,12 @@ "\n", "9. [TEK5040 – Dyp læring for autonome systemer](https://www.uio.no/studier/emner/matnat/its/TEK5040/). 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.\n", "\n", + "## Additional courses of interest\n", + "\n", + "1. [STK4051 Computational Statistics](https://www.uio.no/studier/emner/matnat/math/STK4051/index-eng.html)\n", + "\n", + "2. [STK4021 Applied Bayesian Analysis and Numerical Methods](https://www.uio.no/studier/emner/matnat/math/STK4021/index-eng.html)\n", + "\n", "## Best wishes to you all and thanks so much for your heroic efforts this semester\n", "\n", "\n", diff --git a/doc/pub/summary/pdf/summary-minted.pdf b/doc/pub/summary/pdf/summary-minted.pdf index 9b9b07418..8ff5019d4 100644 Binary files a/doc/pub/summary/pdf/summary-minted.pdf and b/doc/pub/summary/pdf/summary-minted.pdf differ diff --git a/doc/src/Summary/summary.do.txt b/doc/src/Summary/summary.do.txt index e1d048456..8ce7a9cc0 100644 --- a/doc/src/Summary/summary.do.txt +++ b/doc/src/Summary/summary.do.txt @@ -44,11 +44,11 @@ o Principal Component Analysis. ===== Machine learning ===== The following topics will be covered -- Linear methods for regression and classification; -- Boltzmann machines; -- Neural networks; -- Decisions trees and nearest neighbor algorithms -- Support vector machines +o Linear methods for regression and classification; +o Boltzmann machines; +o Neural networks; +o Decisions trees and nearest neighbor algorithms +o Support vector machines !split @@ -83,21 +83,20 @@ ethical conduct is emphasized throughout the course. The link here URL:"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. o "STK2100 Machine learning and statistical methods for prediction and classification":"http://www.uio.no/studier/emner/matnat/math/STK2100/index-eng.html". - o "IN3050 Introduction to Artificial Intelligence and Machine Learning":"https://www.uio.no/studier/emner/matnat/ifi/IN3050/index-eng.html". Introductory course in machine learning and AI with an algorithmic approach. - -o "STK-INF3000/4000 Selected Topics in Data Science:"http://www.uio.no/studier/emner/matnat/math/STK-INF3000/index-eng.html". The course provides insight into selected contemporary relevant topics within Data Science. - +o "STK-INF3000/4000 Selected Topics in Data Science":"http://www.uio.no/studier/emner/matnat/math/STK-INF3000/index-eng.html". The course provides insight into selected contemporary relevant topics within Data Science. o "IN4080 Natural Language Processing":"https://www.uio.no/studier/emner/matnat/ifi/IN4080/index.html". Probabilistic and machine learning techniques applied to natural language processing. - o "STK-IN4300 – Statistical learning methods in Data Science":"https://www.uio.no/studier/emner/matnat/math/STK-IN4300/index-eng.html". An advanced introduction to statistical and machine learning. For students with a good mathematics and statistics background. o "INF4490 Biologically Inspired Computing":"http://www.uio.no/studier/emner/matnat/ifi/INF4490/". An introduction to self-adapting methods also called artificial intelligence or machine learning. o "IN-STK5000 Adaptive Methods for Data-Based Decision Making":"https://www.uio.no/studier/emner/matnat/ifi/IN-STK5000/index-eng.html". Methods for adaptive collection and processing of data based on machine learning techniques. o "IN5400/INF5860 – Machine Learning for Image Analysis":"https://www.uio.no/studier/emner/matnat/ifi/IN5400/". An introduction to deep learning with particular emphasis on applications within Image analysis, but useful for other application areas too. o "TEK5040 – Dyp læring for autonome systemer":"https://www.uio.no/studier/emner/matnat/its/TEK5040/". 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. +!split +===== Additional courses of interest ===== - +o "STK4051 Computational Statistics":"https://www.uio.no/studier/emner/matnat/math/STK4051/index-eng.html" +o "STK4021 Applied Bayesian Analysis and Numerical Methods":"https://www.uio.no/studier/emner/matnat/math/STK4021/index-eng.html" !split ===== Best wishes to you all and thanks so much for your heroic efforts this semester =====