Line 15: | Line 15: | ||

=== TUB === | === TUB === | ||

+ | 1st Semester | ||

+ | * [[Seminar Hot Topics in Information Management IMSEM (TUB)]] | ||

+ | * [[Database Implementation (TUB)]] | ||

* [[Scalable Data Analytics and Data Mining AIM3 (TUB)]] | * [[Scalable Data Analytics and Data Mining AIM3 (TUB)]] | ||

* [[Python for Machine Learning (TUB)]] | * [[Python for Machine Learning (TUB)]] | ||

* [[Machine Learning 1 (TUB)]] | * [[Machine Learning 1 (TUB)]] | ||

+ | |||

+ | 2nd Semester | ||

* [[Machine Learning 2 (TUB)]] | * [[Machine Learning 2 (TUB)]] | ||

− | * [[ | + | * [[Scalable Machine Learning (TUB)]] |

Line 40: | Line 45: | ||

* [[Calculus Single Variable (coursera)]] | * [[Calculus Single Variable (coursera)]] | ||

* [[Information Theory (coursera)]] | * [[Information Theory (coursera)]] | ||

+ | * [[Econometrics: Methods and Applications (coursera)]] | ||

=== [[:Category:edX]] === | === [[:Category:edX]] === | ||

− | * [[Introduction to Probability - The Science of Uncertainty | + | * [[Introduction to Probability - The Science of Uncertainty (edX)]] |

− | * [[Learning From Data | + | * [[Learning From Data (edX)]] |

* [[Introduction to Linear Models and Matrix Algebra (edX)]] | * [[Introduction to Linear Models and Matrix Algebra (edX)]] | ||

* [[Linear Algebra Foundations to Frontiers (edX)]] | * [[Linear Algebra Foundations to Frontiers (edX)]] | ||

Line 53: | Line 59: | ||

− | + | [[Category:edX]] | |

[[Category:Coursera]] | [[Category:Coursera]] | ||

[[Category:IT4BI]] | [[Category:IT4BI]] | ||

− | |||

[[Category:Notes]] | [[Category:Notes]] |

- Advanced Databases (ULB)
- Business Process Management (ULB)
- Data Warehousing (ULB)
- Database Systems Architecture (ULB)
- Decision Engineering (ULB)

- Advanced Data Warehousing (UFRT)
- Data Mining (UFRT)
- XML and Web Technologies (UFRT)
- Information Retrieval (UFRT)
- Business Intelligence Seminar (UFRT)

1st Semester

- Seminar Hot Topics in Information Management IMSEM (TUB)
- Database Implementation (TUB)
- Scalable Data Analytics and Data Mining AIM3 (TUB)
- Python for Machine Learning (TUB)
- Machine Learning 1 (TUB)

2nd Semester

- Computing for Data Analysis (coursera)
- Game Theory (coursera)
- Data Analysis (coursera)
- Algorithms Design and Analysis Part 1 (coursera)
- Functional Programming Principles in Scala (coursera)
- Statistics: Making Sense of Data (coursera)
- Web Intelligence and Big Data (coursera)
- Machine Learning (coursera)
- Introduction to Data Science (coursera)
- Cryptography I (coursera)
- Discrete Optimization (coursera)
- Automata (coursera)
- Mining Massive Datasets (coursera)
- Coding the Matrix (coursera)
- Calculus Single Variable (coursera)
- Information Theory (coursera)
- Econometrics: Methods and Applications (coursera)

- Introduction to Probability - The Science of Uncertainty (edX)
- Learning From Data (edX)
- Introduction to Linear Models and Matrix Algebra (edX)
- Linear Algebra Foundations to Frontiers (edX)
- The Analytics Edge (edX)