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Сергукова Юлия Михайловна
and
Плеханов Михаил Владимирович
Данный курс был создан сотрудниками "Mail.Ru Group". При разработке заданий упор делался на знания и опыт, которые используются сотрудниками на практике ежедневно при проектировании продуктов, которыми пользуются миллионы людей.
В современном мире невозможно представить человека, который, заходя в интернет, не пользуется поисковыми системами. Google, Yandex, Mail.ru и другие интернет-гиганты решают задачи нахождения информации в интернете и удовлетворения информационных потребностей пользователя. В этом курсе мы расскажем вам, как устроена поисковая система изнутри, покажем, какие приемы обработки естественного языка и машинного...
Read more
Данный курс был создан сотрудниками "Mail.Ru Group". При разработке заданий упор делался на знания и опыт, которые используются сотрудниками на практике ежедневно при проектировании продуктов, которыми пользуются миллионы людей.
В современном мире невозможно представить человека, который, заходя в интернет, не пользуется поисковыми системами. Google, Yandex, Mail.ru и другие интернет-гиганты решают задачи нахождения информации в интернете и удовлетворения информационных потребностей пользователя. В этом курсе мы расскажем вам, как устроена поисковая система изнутри, покажем, какие приемы обработки естественного языка и машинного...
Read more
Данный курс был создан сотрудниками "Mail.Ru Group". При разработке заданий упор делался на знания и опыт, которые используются сотрудниками на практике ежедневно при проектировании продуктов, которыми пользуются миллионы людей.
В современном мире невозможно представить человека, который, заходя в интернет, не пользуется поисковыми системами. Google, Yandex, Mail.ru и другие интернет-гиганты решают задачи нахождения информации в интернете и удовлетворения информационных потребностей пользователя. В этом курсе мы расскажем вам, как устроена поисковая система изнутри, покажем, какие приемы обработки естественного языка и машинного обучения используются при построении поискового индекса и ответе на запросы. Также мы обсудим тему объективной оценки качества поисковой системы. В результате слушатели курса смогут опробовать все вышеперечисленные техники на практике и построить работающую модель поисковой системы.
Register for this course and see more details by visiting:
OpenCourser.com/course/9i2jvq/vvedenie
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Suitable for software developers as it provides insights into search engine architecture from a practitioner's lens
Taught by industry professionals from Mail.Ru Group, offering real-world expertise in search engine design and development
Provides hands-on practice in building a search engine model, enabling learners to apply concepts immediately
Save this course
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Reviews summary
Thought-provoking
This course on information retrieval introduces you to search engine fundamentals and dives into natural language processing and machine learning.
Engaging lectures prompt you to consider things from different perspectives.
"Лекторы заставляют подумать."
Technical issues with grading.
"There is no way to finish this course.
For more than 3 years people complain about grader error but with no luck."
Activities
Be better prepared
before
your course. Deepen your understanding
during
and
after
it. Supplement your coursework and achieve mastery of the topics covered
in Введение в информационный поиск with these
activities:
Review Probability Theory
Show steps
Solidify your understanding of probability theory, which is the foundation of many machine learning and data mining techniques.
Browse courses on
Probability Theory
Show steps
-
Go over the basics of probability distributions
-
Practice calculating probabilities of events
-
Review conditional probability and Bayes' theorem
Review foundational material on search algorithms
Show steps
Review core concepts to strengthen understanding before you start the course.
Browse courses on
Search Algorithms
Show steps
-
Review the basics of linked lists, hash tables, and trees, along with their time complexity for insertion, deletion, and retrieval.
-
Go over various search algorithms such as sequential search, binary search, interpolation search, and hash table lookup, and their time and space complexity.
-
Practice solving problems involving basic search algorithms on platforms like LeetCode or HackerRank.
Follow tutorials on Vector Space Models
Show steps
Explore how Vector Space Models are used in information retrieval and natural language processing.
Browse courses on
Vector Space Models
Show steps
-
Find tutorials on Vector Space Models
-
Complete the exercises provided in the tutorials
-
Implement a Vector Space Model from scratch
Eight other activities
Expand to see all activities and additional details
Show all 11 activities
Attend meetups or conferences related to search engines
Show steps
Connect with others in the field, learn about industry trends, and explore job opportunities.
Browse courses on
Networking
Show steps
-
Find and attend meetups or conferences focused on search engine technology.
-
Network with professionals, exchange ideas, and learn about the latest advancements in the field.
-
Explore job opportunities and connect with potential employers.
Solve practice questions on Term Frequency-Inverse Document Frequency (TF-IDF)
Show steps
Reinforce your understanding of TF-IDF, a technique used to determine the importance of words in a document.
Browse courses on
Text Mining
Show steps
-
Find practice questions on TF-IDF
-
Solve the practice questions
-
Analyze your results and identify areas for improvement
Explore tutorials on building search engines
Show steps
Familiarize yourself with the practical aspects of search engine development.
Browse courses on
Search Engine Architecture
Show steps
-
Find and go through tutorials or online courses on building simple search engines using Python or Java.
-
Follow along with the tutorials, implementing the basic functionalities of a search engine.
-
Experiment with different ranking algorithms to understand their impact on search results.
Mentor junior developers interested in search engines
Show steps
Reinforce your understanding by sharing your knowledge and supporting others.
Browse courses on
Mentorship
Show steps
-
Identify opportunities to mentor junior developers or students interested in search engine development.
-
Share your knowledge, provide guidance, and answer their questions.
-
Help them build their skills and prepare for a career in search engine technology.
Develop a presentation on supervised and unsupervised learning
Show steps
Deepen your understanding of supervised and unsupervised learning and their applications.
Browse courses on
Supervised Learning
Show steps
-
Research different supervised and unsupervised learning techniques
-
Create a slide deck that explains the concepts and provides examples
-
Practice presenting your slides
Solve coding problems related to search engine functionality
Show steps
Reinforce your understanding of search engine concepts through practical problem-solving.
Browse courses on
Information Retrieval
Show steps
-
Practice solving coding problems on platforms like LeetCode or HackerRank that focus on search engine functionality.
-
Implement algorithms for tokenization, stemming, and stop word removal.
-
Work on problems involving relevance ranking, such as calculating TF-IDF scores or implementing BM25.
Contribute to open-source search engine projects
Show steps
Gain practical experience and connect with professionals in the field.
Browse courses on
Open Source Software
Show steps
-
Identify open-source search engine projects on platforms like GitHub.
-
Contribute to the project by fixing bugs, improving documentation, or adding new features.
-
Engage with the community, ask questions, and learn from experienced contributors.
Build a simple search engine prototype
Show steps
Apply your knowledge to create a tangible project that demonstrates your understanding.
Browse courses on
Search Engine Development
Show steps
-
Design and implement a simple search engine using a programming language like Python or Java.
-
Build an index of documents, preprocess the text, and implement a search functionality.
-
Incorporate a ranking algorithm to determine the relevance of search results.
Review Probability Theory
Show steps
Solidify your understanding of probability theory, which is the foundation of many machine learning and data mining techniques.
Browse courses on
Probability Theory
Show steps
Show steps
Show steps
- Go over the basics of probability distributions
- Practice calculating probabilities of events
- Review conditional probability and Bayes' theorem
Review foundational material on search algorithms
Show steps
Review core concepts to strengthen understanding before you start the course.
Browse courses on
Search Algorithms
Show steps
Show steps
Show steps
- Review the basics of linked lists, hash tables, and trees, along with their time complexity for insertion, deletion, and retrieval.
- Go over various search algorithms such as sequential search, binary search, interpolation search, and hash table lookup, and their time and space complexity.
- Practice solving problems involving basic search algorithms on platforms like LeetCode or HackerRank.
Follow tutorials on Vector Space Models
Show steps
Explore how Vector Space Models are used in information retrieval and natural language processing.
Browse courses on
Vector Space Models
Show steps
Show steps
Show steps
- Find tutorials on Vector Space Models
- Complete the exercises provided in the tutorials
- Implement a Vector Space Model from scratch
Eight other activities
Expand to see all activities and additional details
Show all 11 activities
Attend meetups or conferences related to search engines
Show steps
Connect with others in the field, learn about industry trends, and explore job opportunities.
Browse courses on
Networking
Show steps
Show steps
Show steps
- Find and attend meetups or conferences focused on search engine technology.
- Network with professionals, exchange ideas, and learn about the latest advancements in the field.
- Explore job opportunities and connect with potential employers.
Solve practice questions on Term Frequency-Inverse Document Frequency (TF-IDF)
Show steps
Reinforce your understanding of TF-IDF, a technique used to determine the importance of words in a document.
Browse courses on
Text Mining
Show steps
Show steps
Show steps
- Find practice questions on TF-IDF
- Solve the practice questions
- Analyze your results and identify areas for improvement
Explore tutorials on building search engines
Show steps
Familiarize yourself with the practical aspects of search engine development.
Browse courses on
Search Engine Architecture
Show steps
Show steps
Show steps
- Find and go through tutorials or online courses on building simple search engines using Python or Java.
- Follow along with the tutorials, implementing the basic functionalities of a search engine.
- Experiment with different ranking algorithms to understand their impact on search results.
Mentor junior developers interested in search engines
Show steps
Reinforce your understanding by sharing your knowledge and supporting others.
Browse courses on
Mentorship
Show steps
Show steps
Show steps
- Identify opportunities to mentor junior developers or students interested in search engine development.
- Share your knowledge, provide guidance, and answer their questions.
- Help them build their skills and prepare for a career in search engine technology.
Develop a presentation on supervised and unsupervised learning
Show steps
Deepen your understanding of supervised and unsupervised learning and their applications.
Browse courses on
Supervised Learning
Show steps
Show steps
Show steps
- Research different supervised and unsupervised learning techniques
- Create a slide deck that explains the concepts and provides examples
- Practice presenting your slides
Solve coding problems related to search engine functionality
Show steps
Reinforce your understanding of search engine concepts through practical problem-solving.
Browse courses on
Information Retrieval
Show steps
Show steps
Show steps
- Practice solving coding problems on platforms like LeetCode or HackerRank that focus on search engine functionality.
- Implement algorithms for tokenization, stemming, and stop word removal.
- Work on problems involving relevance ranking, such as calculating TF-IDF scores or implementing BM25.
Contribute to open-source search engine projects
Show steps
Gain practical experience and connect with professionals in the field.
Browse courses on
Open Source Software
Show steps
Show steps
Show steps
- Identify open-source search engine projects on platforms like GitHub.
- Contribute to the project by fixing bugs, improving documentation, or adding new features.
- Engage with the community, ask questions, and learn from experienced contributors.
Build a simple search engine prototype
Show steps
Apply your knowledge to create a tangible project that demonstrates your understanding.
Browse courses on
Search Engine Development
Show steps
Show steps
Show steps
- Design and implement a simple search engine using a programming language like Python or Java.
- Build an index of documents, preprocess the text, and implement a search functionality.
- Incorporate a ranking algorithm to determine the relevance of search results.
Career center
Learners who complete Введение в информационный поиск will develop knowledge and skills
that may be useful to these careers:
Search Engine Evaluator
Search Engine Evaluator
Search Engine Evaluators assess the quality of search engine results. This course provides a foundation in search engine evaluation and information retrieval. It would be particularly useful for Search Engine Evaluators who want to move into a management role.
Natural Language Processing Engineer
Natural Language Processing Engineer
Natural Language Processing Engineers design and develop systems that can understand and generate human language. This course provides a foundation in natural language processing and machine learning. It would be particularly useful for Natural Language Processing Engineers who want to work on search engine technology.
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers design and develop systems that can learn from data. This course provides a foundation in machine learning and artificial intelligence. It would be particularly useful for Machine Learning Engineers who want to move into a role that focuses on search engine technology.
Knowledge Engineer
Knowledge Engineer
Knowledge Engineers build and maintain systems that can store and retrieve knowledge. This course provides a foundation in knowledge engineering and artificial intelligence. It would be particularly useful for Knowledge Engineers who want to work on search engine technology.
Search Engine Marketing Manager
Search Engine Marketing Manager
Search Engine Marketing Managers plan and execute marketing campaigns that drive traffic to websites from search engines. This course provides a foundation in search engine marketing and digital marketing. It would be particularly useful for Search Engine Marketing Managers who want to move into a leadership role.
Data Science Manager
Data Science Manager
Data Science Managers plan and execute data science projects. This course provides a foundation in data science and project management. It would be particularly useful for Data Science Managers who want to move into a role that focuses on artificial intelligence.
Information Architect
Information Architect
Information Architects organize and label information to make it easy to find and use. This course provides a foundation in information architecture and usability. It would be particularly useful for Information Architects who want to specialize in search engine optimization.
Knowledge Manager
Knowledge Manager
Knowledge Managers develop and implement strategies for managing knowledge within an organization. This course provides a foundation in knowledge management and information science. It would be particularly useful for Knowledge Managers who want to move into a role that focuses on artificial intelligence.
User Experience Researcher
User Experience Researcher
User Experience Researchers study how users interact with products and services. This course provides a foundation in user experience research and human-computer interaction. It would be particularly useful for User Experience Researchers who want to specialize in search engine usability.
Data Scientist
Data Scientist
Data Scientists use their programming and math skills to gather and analyze data. They then communicate their findings to help businesses make better decisions. This course provides a foundation in programming, data analysis, and visualization. It would be particularly useful for Data Scientists who want to move into a role that focuses on artificial intelligence and machine learning.
Information Technology Manager
Information Technology Manager
Information Technology Managers plan and implement technology solutions for businesses. This course provides a foundation in information technology and business management. It would be particularly useful for Information Technology Managers who want to move into a role that focuses on artificial intelligence.
Data Analyst
Data Analyst
Data Analysts collect, clean, and analyze data to help businesses make better decisions. This course provides a foundation in data analysis and programming. It would be particularly useful for Data Analysts who want to move into a role that focuses on machine learning.
Information Specialist
Information Specialist
Information Specialists research, gather, and organize information. This course provides a foundation in information science and information retrieval. It would be particularly useful for Information Specialists who want to move into a role that focuses on information technology.
Web Developer
Web Developer
Web Developers design and develop websites. This course provides a foundation in web development and programming. It would be particularly useful for Web Developers who want to specialize in search engine optimization.
Software Engineer
Software Engineer
Software Engineers design, develop, and maintain software systems. This course provides a foundation in software engineering and programming. It would be particularly useful for Software Engineers who want to move into a role that focuses on artificial intelligence.
For more career information including salaries, visit:
OpenCourser.com/course/9i2jvq/vvedenie
Reading list
We've selected eight books
that we think will supplement your
learning. Use these to
develop background knowledge, enrich your coursework, and gain a
deeper understanding of the topics covered in
Введение в информационный поиск.
Classic in the field of information retrieval. It provides a comprehensive overview of the fundamental concepts and algorithms used in search engines. It valuable reference for anyone who wants to understand how search engines work.
Provides a more modern and practical perspective on information retrieval. It covers topics such as web search, social media search, and mobile search. It good choice for anyone who wants to learn about the latest developments in information retrieval.
Provides a comprehensive overview of natural language processing (NLP). NLP field that deals with the interaction between computers and human (natural) languages. It valuable resource for anyone who wants to learn about the techniques used to process and understand text data.
Save
Provides a practical overview of search engines. It covers topics such as web crawling, indexing, ranking, and evaluation. It valuable resource for anyone who wants to learn about the inner workings of search engines.
Provides a more theoretical overview of information retrieval. It covers topics such as information models, retrieval models, and evaluation measures. It valuable resource for anyone who wants to understand the foundations of information retrieval.
Provides an overview of sentiment analysis. Sentiment analysis field that deals with the analysis of opinions and emotions in text data. It valuable resource for anyone who wants to learn about the techniques used to process and understand text data.
Save
Provides a comprehensive overview of machine learning. It covers topics such as supervised learning, unsupervised learning, and reinforcement learning. It good choice for beginners who want to learn about the basics of machine learning.
Provides a comprehensive overview of information retrieval. It covers topics such as information models, retrieval models, and evaluation measures. It good choice for students who want to learn about the foundations of information retrieval.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/9i2jvq/vvedenie
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Time
6 hours
Via
Coursera
Institutions
Moscow Institute of Physics and Technology
ФРОО
Mail.Ru Group
VK
Instructors
Сергукова Юлия Михайловна
Плеханов Михаил Владимирович
Good to know
Suitable for software developers as it provides insights into search engine architecture from a practitioner's lens
Taught by industry professionals from Mail.Ru Group, offering real-world expertise in search engine design and development
Provides hands-on practice in building a search engine model, enabling learners to apply concepts immediately
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