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  • Foundational Knowledge Needed To Work With Dark Data

Results for "foundational knowledge needed to work with dark data"


  • Status: New
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    Pearson

    Data Science Fundamentals Part 1: Unit 1

    Skills you'll gain: Applied Machine Learning, Data Science, Python Programming, Scikit Learn (Machine Learning Library), NumPy, Computational Thinking, Machine Learning Algorithms, Pandas (Python Package), Data Preprocessing, Data Analysis, Exploratory Data Analysis, Programming Principles, Data Manipulation

    Beginner · Course · 1 - 4 Weeks

  • Status: Free Trial
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    Johns Hopkins University

    Foundations of Data Visualization

    Skills you'll gain: Data Presentation, Graphic and Visual Design, Data Storytelling, Design Elements And Principles, Plot (Graphics), Data Literacy, Exploratory Data Analysis, Scatter Plots

    Intermediate · Course · 1 - 3 Months

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    Coursera

    Building a Real-World Data Science Solution

    Skills you'll gain: AWS SageMaker, Exploratory Data Analysis, Feature Engineering, Dashboard, Data Presentation, Model Evaluation, Data Visualization, Data Pipelines, Project Documentation, Solution Delivery, Amazon Web Services, Data Analysis, Data Integration, Cloud Development, Technical Documentation, Business Intelligence, Cloud Infrastructure, Technical Communication, Automation, Project Management

    Beginner · Course · 1 - 3 Months

  • Status: Free Trial
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    Coursera

    Advanced Quantitative Statistics with Excel

    Skills you'll gain: Regression Analysis, Microsoft Excel, Statistical Hypothesis Testing, Business Analytics, Data-Driven Decision-Making, Excel Formulas, Data Visualization, Data Literacy, Business Analysis, Data Presentation, Business Intelligence, Statistical Analysis, Statistical Methods, Analytics, Spreadsheet Software, Data Analysis, Data Analysis Software, Correlation Analysis, Case Studies, Data Manipulation

    4.8
    Rating, 4.8 out of 5 stars
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    13 reviews

    Beginner · Course · 1 - 4 Weeks

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    Pearson

    Data Science Fundamentals Part 2: Unit 3

    Skills you'll gain: Predictive Modeling, Model Evaluation, Regression Analysis, Scikit Learn (Machine Learning Library), Probability & Statistics, Statistical Inference, Business Analytics, Data Analysis, Statistical Analysis, Probability Distribution, Estimation, Machine Learning

    Beginner · Course · 1 - 4 Weeks

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    Coursera

    Beyond basics: Advanced Data Analysis with Python

    Skills you'll gain: A/B Testing, Statistical Hypothesis Testing, Statistical Methods, Advanced Analytics, Statistical Analysis, Correlation Analysis, Data Analysis, Report Writing, Probability & Statistics, Analytical Skills, Data-Driven Decision-Making, Health Information Management and Medical Records, Business Process Automation

    Beginner · Course · 1 - 4 Weeks

  • C

    Clemson University

    Applied Data Science

    Skills you'll gain: Dimensionality Reduction, Model Evaluation, Data Cleansing, Matplotlib, Regression Analysis, Unsupervised Learning, Data Science, Statistical Analysis, Anomaly Detection, Data Preprocessing, Statistical Methods, Data Analysis, Data Visualization Software, Pandas (Python Package), Exploratory Data Analysis, Machine Learning

    Build toward a degree

    Intermediate · Course · 1 - 3 Months

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    Northeastern University

    Foundations for Data Analytics Part 2

    Skills you'll gain: Time Series Analysis and Forecasting, Correlation Analysis, Probability & Statistics, Text Mining, Statistical Analysis, Probability Distribution, Data Analysis, Network Analysis, Exploratory Data Analysis, Feature Engineering, Data Structures, Unstructured Data, Data Cleansing, Data Preprocessing, Natural Language Processing

    Beginner · Course · 1 - 3 Months

  • Status: Free Trial
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    Packt

    Foundations of Deep Learning and Neural Networks

    Skills you'll gain: Artificial Neural Networks, Deep Learning, Convolutional Neural Networks, Image Analysis, Keras (Neural Network Library), Artificial Intelligence and Machine Learning (AI/ML), Tensorflow, Machine Learning Methods, Network Architecture, Artificial Intelligence, Network Model, Machine Learning, Classification Algorithms, Data Processing

    Intermediate · Course · 1 - 3 Months

  • Status: Free Trial
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    Packt

    Foundations of R Programming and Basic Data Manipulation

    Skills you'll gain: Rmarkdown, R (Software), Data Import/Export, R Programming, Ggplot2, Data Manipulation, Plotly, Data Visualization, Web Scraping, Interactive Data Visualization, Data Visualization Software, Data Cleansing, Data Preprocessing, Data Transformation, Statistical Programming, Programming Principles, Data Structures

    Beginner · Course · 1 - 3 Months

  • Status: Free Trial
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    Packt

    Foundations of Data Analysis with Pandas and Python

    Skills you'll gain: Data Import/Export, Pandas (Python Package), Pivot Tables And Charts, Jupyter, Microsoft Excel, Data Analysis, Data Manipulation, Python Programming, Data Structures, Development Environment, Object Oriented Programming (OOP)

    4.7
    Rating, 4.7 out of 5 stars
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    30 reviews

    Beginner · Course · 1 - 4 Weeks

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    Fractal Analytics

    Advanced Data Techniques for Enterprise AI Systems

    Skills you'll gain: Vector Databases, Data Strategy, Data Management, Data Architecture, Data Security, Data Governance, Generative AI Agents, Metadata Management, Data Ethics, Interoperability, Data Store, Retrieval-Augmented Generation, Embeddings, Taxonomy, Data Storage, Data Processing, Large Language Modeling, Machine Learning, Zero Trust Network Access, Agentic systems

    Intermediate · Course · 1 - 3 Months

1…8910…834

In summary, here are 10 of our most popular foundational knowledge needed to work with dark data courses

  • Data Science Fundamentals Part 1: Unit 1: Pearson
  • Foundations of Data Visualization: Johns Hopkins University
  • Building a Real-World Data Science Solution : Coursera
  • Advanced Quantitative Statistics with Excel: Coursera
  • Data Science Fundamentals Part 2: Unit 3: Pearson
  • Beyond basics: Advanced Data Analysis with Python: Coursera
  • Applied Data Science: Clemson University
  • Foundations for Data Analytics Part 2: Northeastern University
  • Foundations of Deep Learning and Neural Networks: Packt
  • Foundations of R Programming and Basic Data Manipulation: Packt

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