Lawctopus Law School
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Professional Certificate in Data Processing and Analysis by ITMO University [4 Months]: Enroll Now

About the Course

The demand for skilled data analysts both in science and industry is constantly growing. Data processing and analysis Professional Certificate Program gives you the necessary knowledge base and useful skills to face data analysis challenges in your professional field.

The first course of the Program covers such concepts of data analytics as data preprocessing and visualization, large datasets management and storage by means of SQL and NoSQL database management systems, data series analysis.

The second course of the program discusses what machine learning is and mainly focuses on the regression problem (linear regression, polynomial and multivariable regression), classification methods (logistic regression, Naïve Bayes and K-nearest neighbors) and clustering methods (hierarchical and k-means clustering).

The last course covers advanced methods of machine learning. You will learn how to analyze large datasets, find regularities in your data, and apply more complicated clusterization and classification techniques. More precisely, you will face with the concept of the factor analysis under the Principal Component Analysis (PCA), learn about support vector machines (SVM) and decision trees for classification, get familiar with some popular resampling methods and apply them to the so-called Ensemble Learning. Finally, you will deal with the problem of reinforcement learning and learn some useful algorithms.

What you will learn?
  • How to preprocess large datasets before the analysis: data cleaning, data smoothing and normalization methods, correct data visualization techniques and time series analysis.
  • How to store and process the data by means of SQL and NoSQL database management systems.
  • What are the differences between supervised and unsupervised machine learning methods and what is reinforcement learning.
  • What are different classification methods (logistic regression, Naïve Bayes and K-nearest neighbors, SVM) and clustering methods (hierarchical and k-means clustering).
  • How to reduce the number of variables in a dataset and how to evaluate your model.
Syllabus
  • Data Storage & Processing
  • Introduction to Machine Learning
  • Advanced Machine Learning
Fee

₹33,015, For the full program experience.

To enroll in this course, click the link below.

Professional Certificate in Data Processing and Analysis 

Note: Noticebard is associated with Edx through an affiliate programme.

 

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