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Advanced Methods in Data Science and Big Data Analytics

Empower Your Career with Cutting-Edge Data Skills

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  • Nevyžaduje praxi

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Who is the course for

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Who is this course for?

This course is designed for individuals looking to deepen their understanding and enhance their skills in the fields of data science and big data analytics. Whether you are a data professional aiming to upgrade your analytical capabilities or a researcher interested in leveraging large datasets for insightful discoveries, this course offers the advanced tools and techniques necessary for mastering the domain.

The curriculum is particularly beneficial for those who already have a foundational knowledge in statistics, programming, and data manipulation, and are now looking to tackle more complex data problems. By integrating theory with practical case studies, this course prepares participants to effectively handle real-world data challenges in various sectors.

Target audience:

  • Data Scientists and Data Analysts seeking advanced training

  • IT professionals interested in the field of Big Data

  • Academic Researchers and Graduate students in quantitative fields

  • Business Intelligence professionals looking to expand their analytics toolkit

  • Software Engineers looking to transition into Data Science roles

  • Technical Managers overseeing data-driven projects

What will you learn

More information
  • Machine learning techniques
  • Big data processing
  • Predictive analytics
  • Data visualization tools

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This course can be customized - either as an individual training 1:1 or for your team. Just leave us your contact and we will contact you with options tailored to your needs.

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Timeline

Agenda

– Module 1: MapReduce and Hadoop
  • Lesson 1: The MapReduce Framework
  • Lesson 2: Apache Hadoop
  • Lesson 3: Hadoop Distributed File System
  • Lesson 4: YARN
Module 2: Hadoop Ecosystem and NoSQL
  • Lesson 1: Hadoop Ecosystem
  • Lesson 2: Pig
  • Lesson 3: Hive
  • Lesson 4: NoSQL – Not Only SQL
  • Lesson 5: HBase
  • Lesson 6: Spark
Module 3: Natural Language Processing
  • Lesson 1: Introduction to NLP
  • Lesson 2: Text Preprocessing
  • Lesson 3: TFIDF
  • Lesson 4: Beyond Bag of Words
  • Lesson 5: Language Modeling
  • Lesson 6: POS Tagging and HMM
  • Lesson 7: Sentiment Analysis and Topic Modeling
Module 4: Social Network Analysis
  • Lesson 1: Introduction to SNA and Graph Theory
  • Lesson 2: Most Important Nodes
  • Lesson 3: Communities and Small World
  • Lesson 4: Network Problems and SNA ToolsModule 5: Data Science Theory and Methods
  • Lesson 1: Simulation
  • Lesson 2: Random Forests
  • Lesson 3: Multinomial Logistic Regression
Module 6: Data Visualization
  • Lesson 1: Perception and Visualization
  • Lesson 2: Visualization of Multivariate Data Module In addition
  • Block length
  • Teaching hours
  • Refreshments No
  • Exam No

Lecture and demonstrations, the classroom options include handson lab exercises designed to allow practical experience for the participant. The on-demand online course provides recordings of the lab exercises.

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Contains consolidated terms and definitions of thousands of managerial terms in the field of project, program, portfolio, risk, enterprise architecture, security and personal data protection.

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