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    Intro to Big Data, Data Science and Artificial Intelligence

    BY
    Udemy

    Gain a solid understanding of the concepts and functionalities associated with data science, big data, and artificial intelligence.

    Brochure Enquire
    Mode

    Online

    Fees

    ₹ 1299

    Quick Facts

    particular details
    Medium of instructions English
    Mode of learning Self study
    Mode of Delivery Video and Text Based

    Course overview

    The fields of big data, data science, and artificial intelligence are all interconnected in terms of research and technological advancement. Big data technology makes use of AI concepts and methods, and AI depends on abundant data sources and related big data technologies to advance and develop decision-making attributes. Intro to Big Data, Data Science, and Artificial Intelligence online certification is designed by Julia Mariasova- Management Consultant & Media Producer, which is made available through Udemy.

    Intro to Big Data, Data Science, and Artificial Intelligence online training is a self-paced program that comprises 10 articles, 10 downloadable resources, and assignments that are intended for candidates who are interested in big data, machine learning, and artificial intelligence to advance in their professional careers. With Intro to Big Data, Data Science, and Artificial Intelligence online classes, candidates will also be taught about the functionalities of big data and data science in the fields like healthcare, manufacturing, logistics, transportation, real estate, and property management.

    The highlights

    • Certificate of completion
    • Self-paced course
    • 3.5 hours of pre-recorded video content
    • 10 articles
    • 10 downloadable resources
    • Assignments 
    • Quizzes

    Program offerings

    • Online course
    • Learning resources
    • 30-day money-back guarantee
    • Unlimited access
    • Accessible on mobile devices and tv

    Course and certificate fees

    Fees information
    ₹ 1,299
    certificate availability

    Yes

    certificate providing authority

    Udemy

    What you will learn

    Knowledge of big data Data science knowledge Knowledge of artificial intelligence Machine learning Knowledge of cloud computing Knowledge of deep learning Knowledge of algorithms Manufacturing knowledge

    After completing the Intro to Big Data, Data Science, and Artificial Intelligence certification course, candidates will gather a comprehensive understanding of the advanced concepts associated with big data, artificial intelligence, and data science as well as will acquire an understanding of the fundamentals associated with deep learning, cloud computing, machine learning, data analysis, neural networks. In this big data course, candidates will explore the functionality of AI algorithms and ML algorithms as well as will acquire knowledge of the functionalities of NoSQL, connectivity, Hadoop, cloud, and big data analytics. In this data science certification, candidates will also acquire knowledge of the functionalities of big data and data science in manufacturing, transportation, logistics, real estate, property management, and healthcare.

    The syllabus

    Course overview and Introduction to big data

    • Course Introduction
    • Guest Speakers
    • BEFORE YOU START
    • Why learn about big data?
    • Big data definition and Sources of data
    • Big Data Definition
    • New Sources of Data

    Big Data In Practice - Logistics & Transportation

    • Section introduction
    • Logistics & Transportation: Social Impact of Artificial Intelligence & IoT
    • Logistics & Transportation: Predictive & Prescriptive Maintenance
    • Logistics & Transportation: Prepositioning of Goods and Just in Time inventory
    • Logistics & Transportation: Route Optimisation
    • Logistics & Transportation: Warehouse Optimisation and order picking
    • Logistics & Transportation: The Future of the industry
    • Logistics and Transportation Quiz
    • Google Maps News

    Big Data In Practice - Predictive Maintenance In Manufacturing

    • Predictive Maintenance in Manufacturing - Case Study SIBUR
    • Predictive maintenance

    Big Data In Practice: Real Estate & Property Management

    • Real Estate: Introduction to big data in real estate
    • Real Estate: Business Drivers for Using Big Data
    • Real Estate & Property Management: Technological Enablers
    • Real Estate: Building Asset Management and Building Information Modelling
    • Real Estate: Big Data and IoT in Building Maintenance and Management - examples
    • Real Estate: Smart Buildings
    • Additional Resources to Lecture on Smart Buildings
    • Real Estate: Smart Cities (examples - Los Angeles and Hudson Yards in New York)
    • Additional resources on Smart Cities
    • Real Estate: Smart Technologies Cost and Government Subsidies (example - Norway)
    • Real Estate: Data Driven Future
    • Real Estate and Property Management
    • Operational Efficiencies and Sustainability

    Big Data In Practice: Healthcare

    • Healthcare: Data Challenges in Healthcare Industry
    • Healthcare: Transforming Role of AI and Data Measurement Technologies
    • Healthcare: Artificial Intelligence in Disease Prevention
    • Healthcare: Artificial Intelligence in Anti-Ageing
    • Healthcare: AI in Clinical Decision Making and Cancer Treatment
    • Healthcare: Clash of AI and Traditional Healthcare Science
    • Healthcare: Final Remarks - Value of Artificial Intellegence to Consumers
    • BIG DATA IN PRACTICE: SECTION WRAP-UP
    • Healthcare
    • AI in Medical Research

    Data Science And Required Skillset

    • Data Science Definition and Required Skillset
    • Guest Speakers importance of working in teams & understanding business objective
    • Data Science Skillset: Section Wrap-Up
    • Handouts
    • Data Science Skills
    • Data Science and Business Skills

    Introduction To Big Data Technologies

    • Key Technological Advances and Enablers
    • Wide Adoption of Cloud Computing
    • Data Management Technological Breakthroughs (e.g. NoSQL, Hadoop)
    • Open Source and Open APIs
    • Big Data Enablers
    • Additional Resources and Handouts
    • Big Data Technology Architecture (including examples of popular technologies)
    • Big data technology architecture
    • Additional Resources and Handouts
    • Technology Architecture

    Introduction To Data Analysis, Artificial Intelligence And Machine Learning

    • Why to be data and tech savvy
    • Big Data Analytics and Artificial Intelligence Definitions
    • Machine Learning Workflow and Training a Model
    • Model Accuracy and Ability to Generalise
    • Machine Learning Components: DATA
    • Machine Learning Components: FEATURES
    • Machine Learning Components: ALGORITHMS
    • Additional Resources and Handouts
    • Introduction to AI quiz

    Simplified Overview Of Machine Learning Algorithms

    • Classical Machine Learning: Supervised and Unsupervised Learning
    • SUPERVISED LEARNING: Classification
    • Classification: Naive Bayes
    • Classification: Decision Trees
    • Classification: Support Vector Machines (SVM)
    • Classification: Logistic Regression
    • Classification: K Nearest Neighbour
    • Classification: Anomaly Detection
    • SUPERVISED LEARNING: Regression
    • Classical Machine Learning: Unsupervised Learning
    • UNSUPERVISED LEARNING: Clustering
    • Clustering: K-Means
    • Clustering: Mean-Shift
    • Clustering: DBSCAN
    • Clustering: Anomaly Detection
    • UNSUPERVISED LEARNING: Dimensionality Reduction
    • UNSUPERVISED LEARNING: Association Rule
    • CLASSICAL MACHINE LEARNING - Section Wrap Up
    • REINFORCEMENT LEARNING
    • ENSEMBLES
    • Machine Learning Quiz

    Introduction To Deep Learning And Neural Networks

    • DEEP LEARNING AND NEURAL NETWORKS
    • NEURAL NETWORKS: Convolutional Neural Network
    • NEURAL NETWORKS: Recurrent Neural Network
    • NEURAL NETWORKS: Generative Adversarial Network (GAN)
    • Additional Resources
    • Neural Networks Quiz

    Machine Learning Sections Wrap-Up

    • Machine Learning Algorithms Use Cases
    • Choosing AI algorithms
    • Additional Resources and Handouts
    • Course Wrap up
    • Your feedback and more resources

    Instructors

    Ms Julia Mariasova

    Ms Julia Mariasova
    Management Consultant
    Freelancer

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