Machine Learning is one of the growing markets in the world. It is widely used almost everywhere, it probably uses it more times without knowing it. In this decade, machine learning with practical speech recognition, object detection, effective network search, autonomous robots, etc. Using the Python programming language).
LANGUAGE PYTHON and R
- numerical calculations and programming in Python
- statistical analysis in R language
- types of neural networks and their applications
MS AZURE ENVIRONMENT
- writing scripts in the Python programming language
- building simple machine models using the MS Azure environment
- A solution supporting the analysis and description of the natural language
- A solution supporting Big Data analysis and printing
- completed or during the course of study:
- mathematics / statistics / physics / computer science /
- chemia teoretyczna / automatyka i robotka / mechatronics / electronics
- and telecommunications / biomedical engineering
- insight into topics such as: mathematical analysis, linear algebra, probability calculus and statistics, mathematical logic, numerical methods
- min. 2 years of working with working data, including data analyst, BI, statistics, Big Data, etc.
- specialist knowledge with data analysis and modeling, BI, big data
programming experience and knowledge of technology
- knowledge of the English language
- solid basics of programming in one voice
- basics of linear algebra
- derivatives, multi-user functions, differential calculus
basics of calculus of probability and statistic
- basics of discrete mathematics (graph theory),
- basics of cloud technologies, basics of distributed computing, programming skills in Python and / or R, basics of data mining and / or big data.
In this module you gain the ability to write scripts in the Python programming language. You will learn to build a simple machine model using the MS Azure environment. You will be able to solve problems at every stage of preparation and implementation of programs and under. After the main module you will:
Writing correctly formatted and documented scripts in Python and solving problems that arise when writing them
Have the ability to train machine patterns data stored in various input formats to learning sets
Be able to implement using the function of calculating data consumption for selected data sets
Be able to prepare, implement and verify computer programs in Python that process natural language
Be able to perform the entire process associated with the initial processing of model data, model integration with new data
Calculation methods in Python
You will learn the basic elements of Python (data types, operators, loops, conditional statements, input / output operations) and the types and causes of numeric errors. You will be able to correctly format and document the code and solve problems. Differential. Differential. We gained knowledge about the methods of interpolation, the whole, the basics of linear and nonlinear methods, integration, the basis of methods.
|40||Introduction to Programming Using Python 98-381
|Introduction to Machine Learning |
You will know and distinguish classic machine data for analysis. You will understand the problems of overfilling the machine model. You will work in the MS Azure environment for model training.
|Machine learning and neural networks|
We will know the methods of neural machines and networks, we understand their mathematical foundations and applied machine methods to real problems. You will be able to implement or use the machine's algorithmic library. The ability to learn results. Positioning requires the use of a machine algorithm in the problem of automatic understanding of data. You will understand how it develops.
|NLP natural language processing ||30|
|Designing and implementing Big Data solutions|
You will have in-depth knowledge of how to effectively solve large data processing problems (Big Data) You will be able to prepare, implement and verify computer programs that process data in a distributed environment. You will acquire oreinetation in current directions of development of programming languages used to build Big Data support tools.
|40||Designing and Implementing Big Data Analytics Solutions Exam 70-475|