Search result for Exploratory data analysis example Online Courses & Certifications
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Advanced Data Science Techniques in SPSS
by Bogdan Anastasiei- 3.9
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6.5 hours on-demand video
Hone your SPSS skills to perfection - grasp the most high level data analysis methods available in the SPSS program. Within a few days only you can master some of the most complex data analysis techniques available in the SPSS program. Afterwards, the analysis is executed on a real-life data set and the output is thoroughly explained....
$12.99
Calculus through Data & Modeling: Limits & Derivatives
by Joseph W. Cutrone, PhDTop Instructor- 4.8
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Approx. 10 hours to complete
This fundamental notion will be applied through the modelling and analysis of data....
Natural Language Processing with Python and NLTK
by Dr. Ali Feizollah- 3.8
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3 hours on-demand video
Learn how to pre-process your text data and build topic modeling, text summarization and sentiment analysis applications Pre-processing your text data before feeding it to an algorithm is a crucial part of NLP. Sentiment analysis in Python is a very popular application that can be used on variety of text data....
$12.99
Data Science for Business Innovation
by Marco Brambilla , Emanuele Della Valle- 4.2
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Approx. 7 hours to complete
The course is a compendium of the must-have expertise in data science for executive and middle-management to foster data-driven innovation. It consists of introductory lectures spanning big data, machine learning, data valorization and communication. How Does It Relate to Data Science? How Does It Relate to Data Science? Big Data and Data Science...
Data Science and Machine Learning using Python - A Bootcamp
by Dr. Junaid Qazi, PhD- 4.4
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25 hours on-demand video
This is one of the most comprehensive course on any e-learning platform (including Udemy marketplace) which uses the power of Python to learn exploratory data analysis and machine learning algorithms. This is the time to get into this field with the knowledge and in-depth skills of data analysis and presentation. Pandas for Data Analysis...
$12.99
Foundations of marketing analytics
by Arnaud De Bruyn- 4.6
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Approx. 6 hours to complete
This course is designed for students, business analysts, and data scientists who want to apply statistical knowledge and techniques to business contexts. You will find this course exciting and rewarding if you already have a background in statistics, can use R or another programming language and are familiar with databases and data analysis techniques such as regression, classification, and clustering....
Evaluation of Digital Health Interventions
by Lisa Danquah , Céire Costelloe- 0.0
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Approx. 32 hours to complete
This module focuses on key data considerations for digital health including data management, data visualisation and methods for evaluating digital health interventions. Data and Digital Health - Why is it important? Types of data in Digital Health Data Requirements and Considerations for Digital Health Data Management (Video) Visualising big data to tackle antimicrobial resistance...
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Computer Vision In Python! Face Detection & Image Processing
by Emenwa Global- 4.1
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11 hours on-demand video
For example, medical imaging includes substantial work on the analysis of image data in medical applications. A computer can then read the data from the strain gauges and measure if one or more of the pins is being pushed upward. This sort of technology is useful in order to receive accurate data of the imperfections on a very large surface....
$11.99
Data Wrangling, Analysis and AB Testing with SQL
by Katrina Glaeser- 3.4
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Approx. 16 hours to complete
We'll select and perform the optimal JOIN for a data science inquiry and clean data within an analysis dataset by deduping, running quality checks, backfilling, and handling nulls. Finally, given a predictive analysis need, we'll engineer a feature from raw data using the tools and skills we've built over the course....
Introduction to Big Data
by Ilkay Altintas , Amarnath Gupta- 4.6
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Approx. 17 hours to complete
It provides an introduction to one of the most common frameworks, Hadoop, that has made big data analysis easier and more accessible -- increasing the potential for data to transform our world! * Explain the V’s of Big Data (volume, velocity, variety, veracity, valence, and value) and why each impacts data collection, monitoring, storage, analysis and reporting....
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