What skills will be developed in the course?

The Complex Data Mining Extension Course (MDC) aims to train professionals for the current job market, with an emphasis on: (1) improving data management with speed, capacity and scalability in mind; (2) develop techniques for visualizing these data; (3) finding new business opportunities; (4) improving the data analysis capacity; and (5) create predictive models using the most modern machine learning methods.


Extension course

Email: mdc@ic.unicamp.br

Phone: (19) 3521-5883

Presented by:

About the course


The Extension Course in Complex Data Mining (MDC) consists of 9 subjects that teach the main concepts required by the job market, making a total workload of 180 hours, with 144 hours of classes and 36 hours of supervised activities.


Students approved in the 9 subjects will be entitled to the certificate of the Extension Course in Complex Data Mining (MDC), issued by the Extension School of Unicamp.


The faculty of the Extension Course in Complex Data Mining (MDC) is composed of professors and researchers from Unicamp, all with doctorates.

Remedying the impacts of COVID-19

As inscriptions can be done completely online.
Candidates approved in the Selection Process will receive by email the list of additional documents that must be sent to effect the enrollment in the course.
The course will be held 100% online (including classes, consultations and evaluations).

  • Disciplines

  • DATA ANALYSIS (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: 29/01/2022, 05/02/2022, 12/02/2022 and 19/02/2022, from 08:30 am to 12:30 pm.

    INFORMATION RECOVERY (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: 29/01/2022, 05/02/2022, 12/02/2022 and 19/02/2022, from 13:30 am to 17:30 pm.

    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: 05/03/2022, 12/03/2022, 19/03/2022 and 26/03/2022, 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: 05/03/2022, 12/03/2022, 19/03/2022 and 26/03/2022, from 08:30 pm to 12:30 pm.

    VIEWING INFORMATION (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: 02/04/2022, 09/04/2022, 23/10/2022 and 30/04/2022, 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: 02/04/2022, 09/04/2022, 23/10/2022 and 30/04/2022, 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: 07/05/2022, 14/05/2022, 21/05/2022 and 28/05/2022, from 08:30 am to 12:30 pm.

    DEEP LEARNING (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: 07/05/2022, 14/05/2022, 21/05/2022 and 28/05/2022, 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: 25/06/2022, 02/07/2022, 09/07/2022 and 16/07/2022, from 08:30 am to 12:30 pm.

  • 100% Online Course

  • Our course is not a traditional distance learning course (EAD), 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. The evaluations will be carried out through practical work that must be submitted through the course's own platform.

  • Registration

  • The following documents are required for registration:

    Registration Form and signed Term of Commitment (documents generated by the Online Pre-Registration)
    RG and CPF
    Graduation Diploma (front and back) or Graduation Course Completion Certificate
    Scholar graduation transcripts
    Cover letter (optional, free format, one page)

    Digital copies of the documents listed above must be sent by email to the Extension Secretariat of the Unicamp Computing Institute (itext@unicamp.br), with the subject "MDC - Registration Documents" until 12/12/2021 (Sunday).


    Documents must be received by email by the Extension Office by 12/12/2021 (Sunday).
    In case of doubts about the registration documentation, consult the Extension Secretariat (itext@unicamp.br).
    Late registration will not be accepted.

  • Pricing

  • The total amount of the course can be paid, via bank slip, in 3 ways:
    Interest-free, in 5 monthly installments of R $ 1.799,99, the first maturing on 10/01/2022.
    With a 5% discount, in three monthly installments of R $ 2.849,98, the first maturing on 10/01/2022.
    In cash, with a discount of R $ 1000,00, in the amount of R $ 7.999,95, with maturity on 10/01/2022.

    Observation: the 5% discount for payment in three installments will be applied to the issue of slips.

  • Information

  • Prerequisite: Complete top level. Basic knowledge of programming logic.
    Target Audience: Computer professionals, trained in Computing or related areas (Engineering or Exact).
    Selection criteria: Analysis of Curriculum and School History.
    Course type: Extension course.
    Class schedules: Saturdays, from 8:30 am to 12:30 pm and from 13:30 pm to 17:30 pm.
    Required Material: 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.
    Class size: A minimum of 25 and a maximum of 90 students.
    Course coordinator: Zanoni Days.
    Course teachers: Anderson de Rezende Rocha, Celmar Guimarães da Silva, Esther Luna Colombini, Helio Pedrini, Lin Tzy Li, Lucas Francisco Wanner, Sandra Eliza Fontes from Avila, Zanoni Days.

  • Calendar

  • Data Event
    04/10/2021 até 12/12/2021 Registration period
    12/12/2021 Deadline for submission of registration documents
    17/12/2021 Disclosure of candidates selected for registration
    10/01/2022 Maturity of the first or single installment
    29/01/2022 até 16/07/2022 Course offering period