Online Course – Certified Professional Internship in Natural Language Processing from Universidad Austral

Learn to develop in NLP. Create your own personal NLP workspace.

Suggested by: Coursera (What is Coursera?)

Start your Coursera.com free trial today
קורס אונליין - התמחות מקצועית מוסמכת ב-Natural Language Processing של Universidad Austral

Professional Certificate

Beginners

No prior knowledge required

Time to complete the course

7-day free trial

No unnecessary risks

Skills you will acquire in the course

  • Python programming
  • Application development
  • Natural language processing
  • Data Science

What you will learn in the course

Courses for which the course is suitable

  • Natural Language Processing Application Developer
  • Data Engineer
  • Machine learning model developer
  • Data Analyst
  • Software developer
  • Natural Language Processing Expert
  • Natural language processing workspace developer
  • Project Manager in the field of Natural Language Processing

Internship – a series of 4 courses

This program will allow you to acquire basic, intermediate, and intermediate-advanced knowledge in the field of developing applications based on natural language processing. These applications can be integrated into other applications or used independently. In addition, you will be able to acquire the knowledge required to build your own workspace for natural language processing.

Practical learning project

The overall goal of the projects is to design, test, and implement systems based on this model in the Python language:

  • In course 1

    You will create a basic model to automatically classify text. This model will be given a set of documents to train, and once the model is trained, you can present it with a new document and it will classify it based on the training data.

  • In course 2

    Develop a data cleaning framework suitable for natural language processing.

  • In course 3

    Create a workspace for comparing different models of natural language processing algorithms.

  • In course 4

    You will create the infrastructure required to move a natural language processing project to a production environment, in addition to considering the needs for retraining the model.

Details of the courses that make up the specialization

Introduction to Natural Language Processing

  • Course 1 • 13 hours • 4.4 (25 ratings)

Course Details

What you’ll learn
  • Understand the fundamentals of natural language processing
  • Create text classifications automatically
  • Automatically infer the sentiment of text
  • Automatically extract information from text
Skills you will gain
  • Category: Task chain
  • Category: Emotion Analysis
  • Category: Text Classification
  • Category: Information Publishing
  • Category: Natural Language Processing

Data cleaning for natural language processing

  • Course 2 • 12 hours • 4.3 (14 ratings)

Course Details

What you’ll learn
  • This course will provide you with the knowledge required to extract, clean, and prepare various data sources that will enter the NLP process.
  • Basic to intermediate programming knowledge is required, a basic understanding of the Python language is desirable, and it is advisable to be familiar with the Jupyter Notebooks environment in the Anaconda environment.
Technical requirements
  • To open applications, you must use Python 3.6 or higher. Alternatively, you can use the Anaconda environment with the same version of Python.
  • As a code editor, the examples will be edited in Anaconda Notebook, but the student can use any text editor that supports Anaconda Notebooks.
  • Libraries that need to be installed to complete the course: NLTK, Pandas, Scikit-learn, and data extraction libraries.

NLP models and algorithms

  • Course 3 • 10 hours

Course Details

What you’ll learn
  • This course will provide you with the knowledge required to apply NLP algorithms. Using the latest and most popular algorithms in the field, a solution will be provided to a variety of unique problems in the field.
  • Basic to intermediate programming knowledge is required, basic knowledge of the Python language is also desirable, and it is advisable to be familiar with Jupyter Notebooks in the Anaconda environment.
Technical requirements
  • To open applications, you must use Python 3.6 or higher. Alternatively, you can use the Anaconda environment with the same version of Python.
  • As a code editor, the examples will be edited in Anaconda Notebook, but the student can use any text editor that supports Anaconda Notebooks.
  • Libraries that need to be installed to complete the course: NLTK, Scikit-learn, Spacy, and TensorFlow.

NLP and DevOps System Architecture

  • Course 4 • 10 hours

Course Details

What you’ll learn
  • This course will provide you with the knowledge required to apply NLP algorithms. Using the latest and most popular algorithms in the field, a solution will be provided to a variety of unique problems in the field.
  • Basic to intermediate programming knowledge is required, basic knowledge of the Python language is also desirable, and it is advisable to be familiar with Jupyter Notebooks in the Anaconda environment.
Technical requirements
  • To open applications, you must use Python 3.6 or higher. Alternatively, you can use the Anaconda environment with the same version of Python.
  • As a code editor, the examples will be edited in Anaconda Notebook, but the student can use any text editor that supports Anaconda Notebooks.
  • Libraries that need to be installed to complete the course: NLTK, Scikit-learn, Spacy, and TensorFlow.

Related products