(INF-0612 - Messing with Data)
Teacher: Zanoni Dias
Introduction to Data Analysis using the R Language. Data types (vectors, lists, matrices, data frames, etc.). Predefined functions. Implementation of functions in R. Treatment, analysis and visualization of data.
Classes: 27/01/2024, 03/02/2024, 10/02/2024 and 17/02/2024, from 08:30 am to 12:30 pm.
(INF-0611 - Gathering Data)
Teacher: Lin Tzy Li
Introduction to information retrieval. Ranking evaluation techniques. Unstructured data recovery concepts. Text recovery. Image recovery by content. Video recovery. Techniques for improving ranking quality.
Classes: 27/01/2024, 03/02/2024, 10/02/2024 and 17/02/2024, from 13:30 pm to 17:30 pm.
MACHINE LEARNING NOT SUPERVISED
(INF-0613 - Exploring Data)
Teacher: Hélio Pedrini
Discovery of knowledge. Understanding and prospecting for information. Exploratory data analysis. Anomaly detection. Association rules. Dimensionality reduction. Attribute selection. Grouping techniques.
Classes: 24/02/2024, 02/03/2024, 09/03/2024 and 16/03/2024, from 13:30 pm to 17:30 pm.
SUPERVISED MACHINE LEARNING I
(INF-0615 - Learning from Data)
Teacher: Anderson de Rezende Rocha
Classification problems. Decision boundaries. Linear and non-linear classifiers, logistic regression, decision trees and random forests. Overfitting and validation. Ensemble methods: bagging, boosting and stacking. Cross validation. Imbalance, diagnosis of bias and variance. Evaluation measures. Interpretation of models (X-AI) and classification in open scenario (open-set).
Classes: 24/02/2024, 02/03/2024, 09/03/2024 and 16/03/2024, from 08:30 pm to 12:30 pm.
(INF-0614 - Viewing data)
Teacher: Celmar Guimarães da Silva
Theoretical and practical aspects of Information Visualization (InfoVis). Representation of data in a graphic and interactive way. InfoVis reference model. Characterization of data. Recommendations for visual mapping. Visualization of multidimensional data. Visualization of texts.
Classes: 23/03/2024, 06/04/2024, 13/04/2024 and 20/04/2024, from 08:30 am to 12:30 pm.
SUPERVISED MACHINE LEARNING II
(INF-0616 - Thinking with Data I)
Teacher: Esther Luna Colombini
Vector Support Machines (SVMs): kernels (linear and non-linear), SVRs and one-class SVM. Regularization techniques. Grid-search and random-search. Neural networks: types of networks, forward and backward propagation, and activation functions. Statistical tests.
Classes: 23/03/2024, 06/04/2024, 13/04/2024 and 20/04/2024, from 13:30 am to 17:30 pm.
BIG DATA (INF-0617 - Big Data)
Teacher: Lucas Francisco Wanner
Introduction to parallel and distributed computing. Parallel data processing in Python. Distributed data processing with Map-Reduce and Hadoop Streaming. Introduction to tools for analyzing and processing data with Hadoop and Spark.
Classes: 27/04/2024, 04/05/2024, 11/05/2024 and 18/05/2024, from 08:30 am to 12:30 pm.
(INF-0618 - Thinking with Data II)
Teacher: Sandra Eliza Fontes de Avila
Deep learning and convolutional neural networks (CNN). Convolution: padding and stride. Loss functions. Training: activation, pre-processing, data augmentation, weight initialization and parameter optimization functions. Regularization. Learning transfer. Recurrent Neural Networks (RNN). Transformers. Detection and Segmentation. Generative Adversarial Networks (GAN). Interpretability (X-AI). Tools: TensorFlow and Keras.
Classes: 27/04/2024, 04/05/2024, 11/05/2024 and 18/05/2024, from 13:30 am to 17:30 pm.
FINAL PROJECT (INF-0619 - Data @ Work)
Teacher: Zanoni Dias
Definition of target problem. Data identification and collection. Analysis of the techniques to be employed. Comparative study. Analysis, visualization and presentation of results.
Classes: 08/06/2024, 15/06/2024, 22/06/2024 and 29/06/2024, from 08:30 am to 12:30 pm.
100% Online Course
Our course is not a traditional distance learning (EAD) course (with recorded or pre-recorded classes). All classes will be held and broadcast live (via Zoom), with the participation of students in real time, on the days and times indicated above. Assessments will be carried out through practical assignments. Course material (slides, tutorials, codes, etc.) will be made available to students (via Moodle). Questions will be answered from Monday to Friday, with teachers and monitors, synchronously (via Zoom) and asynchronous (via Slack).
Registration for the class of the first semester of 2024 from 02/10/2023.
The following documents are required for registration:
Registration Form and Term of Commitment digitally signed (documents generated by the Online Pre-Registration)
Diploma or Certificate of Completion of Undergraduate Course
RG and CPF
Cover letter (optional, free format, one page, attach to CV, to be sent through the system)
The documents listed above must be presented on both sides, whenever there is any information recorded on the back of the document.
Documents must be received by the Extecamp system by 15/12/2023 (Friday).
In case of doubts about the registration documentation, consult the Extension Secretariat (email@example.com).
Late registration will not be accepted.
Tuition & Fees
The total cost of the course (R$8.999,95) can be paid in 5 interest-free installments.
Special discounts (cumulative):
R$2.000,00 discount for cash payment.
R$1.000,00 discount for payment in 3 installments without interest.
R$1.000,00 discount for former Unicamp students.
R$2.000,00 discount for registrations made until 31/10/2023.
R$1.000,00 discount for registrations made between 01/11/2023 and 30/11/2023.
The discounts mentioned above will be applied manually when issuing bank slips, after the selection process (the system may display amounts without discounts at the time of registration).
The payment of the first monthly installment or the single installment, depending on the payment method chosen, must be made by 10/01/2024.
To qualify for the early registration discount, all documents must be delivered by the dates indicated.
To qualify for the discount for Unicamp alumni, the candidate must present, at the time of registration, a diploma or a certificate of completion of an undergraduate or graduate course (master's or doctorate) issued by Unicamp.
As the discounts are cumulative, it is possible to obtain up to R$5.000,00 of discount (considering the discounts listed above, applying the respective conditions).
Full upper level. Basic programming knowledge.
Computer professionals, trained in Computing or related areas (Engineering or Exact).
Analysis of Curriculum and Cover Letter (optional).
Saturdays, from 8:30 am to 12:30 pm and from 13:30 pm to 17:30 pm.
As it is a course with a practical focus, all students must have a computer / notebook with internet access to follow the classes and proposed practical activities.
A minimum of 20 and a maximum of 90 students.
Course coordinator: Zanoni Days
|02/10/2023 até 15/12/2023
||Deadline for submission of registration documents
||Disclosure of candidates selected for registration
||Maturity of the first or single installment
|27/01/2024 até 29/06/2024
||Course offering period