Complete Data Wrangling & Data Visualisation In R

THIS IS YOUR ROADMAP TO LEARNING & BECOMING HIGHLY PROFICIENT IN DATA PREPROCESSING, DATA WRANGLING, & DATA VISUALIZATION IN R!

Hello, My name is Minerva Singh. I am an Oxford University MPhil graduate in Geography & Environment & I  finished a PhD at Cambridge University in Tropical Ecology & Conservation.

I have +5 of experience in analyzing real-life data from different sources using statistical modelling and producing publications for international peer-reviewed journals. If you find statistics books & manuals too vague, expensive & not practical, then you’re going to love this course!

I created this course to take you by hand and teach you all the concepts, and tackle the most fundamental building block on practical data science - data wrangling and visualisation.

THIS COURSE WILL TEACH YOU ALL YOU NEED AND PUT YOUR KNOWLEDGE TO PRACTICE NOW!

This course is your sure-fire way of acquiring the knowledge and statistical data analysis wrangling and visualisation skills that I acquired from the rigorous training I received at 2 of the best universities in the world, the perusal of numerous books and publishing statistically rich papers in the renowned international journal like PLOS One.

HERE IS WHAT THIS COURSE WILL DO FOR YOU:

It will take you (even if you have no prior statistical modelling/analysis background) from a basic level of performing some of the most common data wrangling tasks in R.

It will equip you to use some of the most important R data wrangling and visualisation packages such as dplyr and ggplot2.

It will Introduce some of the most important data visualisation concepts to you in a practical manner such that you can apply these concepts for practical data analysis and interpretation.

You will also be able to decide which wrangling and visualisation techniques are best suited to answer your research questions and applicable to your data and interpret the results..

The course will mostly focus on helping you implement different techniques on real-life data such as Olympic and Nobel Prize winners

After each video, you will learn a new concept or technique which you may apply to your own projects immediately! Reinforce your knowledge through practical quizzes and assignments.

ON TOP OF THE COURSE, I’M ALSO OFFERING YOU:

Practice Activities To Reinforce Your Learning

My Continuous Support To Make Sure You Gain Complete Understanding & Proficiency

Access To Future Course Updates Free Of Charge

I’ll Even Go The Extra Mile & Cover Any Topics That Are Related To The Subject That You Need Help With (This is something you can’t get anywhere else).

& Access To A Community Of 25,000 Data Scientists (& growing) All Learning Together & Helping Each Other!

Now, go ahead & enrol in the course. I’m certain you’ll love it, but in case you don’t, you can always request a refund within 30 days. No hard feelings whatsoever. I look forward to seeing you inside!

Who this course is for:

• Students Interested In Getting Started With Data Science Applications In The R & R Studio Environment
• Students Interested in Learning About the Common Pre-processing Data Tasks: Including Cleaning and Munging
• Students Interested in Gaining Exposure to Common R Packages Such As ggplot2
• Those Interested in Learning About Different Kinds of Data Visualisations
• Those Interested in Learning to Create Publication Quality Visualisations

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Complete Data #Wrangling & #Data #Visualisation In R
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Complete Data Wrangling & Data Visualisation In R

Complete Data Wrangling & Data Visualisation In R

The Fun and Easy Guide to Machine Learning using Keras

Welcome to the Fun and Easy Machine learning Course in Python and Keras.
 

Are you Intrigued by the field of Machine Learning? Then this course is for you! We will take you on an adventure into the amazing of field Machine Learning. Each section consists of fun and intriguing white board explanations with regards to important concepts in Machine learning as well as practical python labs which you will enhance your comprehension of this vast yet lucrative sub-field of Data Science.

So Many Machine Learning Courses Out There, Why This One?

This is a valid question and the answer is simple. This is the ONLY course on Udemy which will get you implementing some of the most common machine learning algorithms on real data in Python. Plus, you will gain exposure to neural networks (using the H2o framework) and some of the most common deep learning algorithms with the Keras package.

We designed this course for anyone who wants to learn the state of the art in Machine learning in a simple and fun way without learning complex math or boring explanations.  Each theoretically lecture is uniquely designed using whiteboard animations which can maximize engagement in the lectures and improves knowledge retention. This ensures that you absorb more content than you would traditionally would watching other theoretical videos and or books on this subject.

What you will Learn in this Course

This is how the course is structured:

Regression – Linear Regression, Decision Trees, Random Forest Regression,

Classification – Logistic Regression, K Nearest Neighbors (KNN), Support Vector Machine (SVM) and Naive Bayes,

Clustering - K-Means, Hierarchical Clustering,

Association Rule Learning - Apriori, Eclat,

Dimensionality Reduction - Principle Component Analysis, Linear Discriminant  Analysis,

Neural Networks - Artificial Neural Networks, Convolution Neural Networks, Recurrent Neural Networks.

Practical Lab Structure
You DO NOT need any prior Python or Statistics/Machine Learning Knowledge to get Started. The course will start by introducing students to one of the most fundamental statistical data analysis models and its practical implementation in Python- ordinary least squares (OLS) regression. Subsequently some of the most common machine learning regression and classification techniques such as random forests, decision trees and linear discriminant analysis will be covered. In addition to providing a theoretical foundation for these, hands-on practical labs will demonstrate how to implement these in Python. Students will also be introduced to the practical applications of common data mining techniques in Python and gain proficiency in using a powerful Python based framework for machine learning which is Anaconda (Python Distribution). Finally you will get a solid grounding in both Artificial Neural Networks (ANN) and the Keras package for implementing deep learning algorithms such as the Convolution Neural Network (CNN). Deep Learning is an in-demand topic and a knowledge of this will make you more attractive to employers.

Excited Yet?

So as you can see you are going to be learning to build a lot of impressive Machine Learning apps in this 3 hour course. The underlying motivation for the course is to ensure you can apply Python based data science on real data into practice today. Start analyzing  data for your own projects, whatever your skill level and IMPRESS your potential employers with an actual examples of your  machine learning abilities.

It is a practical, hands-on course, i.e. we will spend some time dealing with some of the theoretical concepts related to data science. However, majority of the course will focus on implementing different  techniques on real data and interpret the results. After each video you will learn a new concept or technique which you may apply to your own projects.

TAKE ACTION TODAY! We will personally support you and ensure your experience with this course is a success. And for any reason you are unhappy with this course, Udemy has a 30 day Money Back Refund Policy, So no questions asked, no quibble and no Risk to you. You got nothing to lose. Click that enroll button and we’ll see you in side the course.

Who this course is for:

• Student who starting out or interested in Machine Learning or Deep Learning.
• Students with Prior Python Programming Exposure Who Want to Use it for Machine Learning
• Students interested in gaining exposure to the Keras library for Deep Learning.
• Data analysts who want to expand into Machine Learning.
• College students who want to start a career in Data Science.

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Clustering & Classification With Machine Learning In Python

HERE IS WHY YOU SHOULD TAKE THIS COURSE:

This course your complete guide to both supervised & unsupervised learning using Python. This means, this course covers all the main aspects of practical data science and if you take this course, you can do away with taking other courses or buying books on Python based data science.

In this age of big data, companies across the globe use Python to sift through the avalanche of information at their disposal..

By becoming proficient in unsupervised & supervised learning in Python, you can give your company a competitive edge and boost your career to the next level.

LEARN FROM AN EXPERT DATA SCIENTIST WITH +5 YEARS OF EXPERIENCE:

My name is Minerva Singh and I am an Oxford University MPhil (Geography and Environment) graduate. I also just recently finished a PhD at Cambridge University.

I have several years of experience in analyzing real life data from different sources  using data science techniques and producing publications for international peer reviewed journals.

Over the course of my research I realized almost all the Python data science courses and books out there do not account for the multidimensional nature of the topic .

This course will give you a robust grounding in the main aspects of machine learning- clustering & classification.

Unlike other Python instructors, I dig deep into the machine learning features of Python and gives you a one-of-a-kind grounding in Python Data Science!

You will go all the way from carrying out data reading & cleaning  to machine learning to finally implementing simple deep learning based models using Python

THE COURSE COMPOSES OF 7 SECTIONS TO HELP YOU MASTER PYTHON MACHINE LEARNING:

• A full introduction to Python Data Science and powerful Python driven framework for data science, Anaconda • Getting started with Jupyter notebooks for implementing data science techniques in Python  • Data Structures and Reading in Pandas, including CSV, Excel and HTML data • How to Pre-Process and “Wrangle” your Python data by removing NAs/No data, handling conditional data, grouping by attributes, etc.

• Machine Learning, Supervised Learning, Unsupervised Learning in Python

• Artificial neural networks (ANN) and Deep Learning. You’ll even discover how to use artificial neural networks and deep learning structures for classification!

With such a rigorous grounding in so many topics, you will be an unbeatable data scientist by the end of the course.

NO PRIOR PYTHON OR STATISTICS OR MACHINE LEARNING KNOWLEDGE IS REQUIRED:

You’ll start by absorbing the most valuable Python Data Science basics and techniques.

I use easy-to-understand, hands-on methods to simplify and address even the most difficult concepts in Python.

My course will help you implement the methods using real data obtained from different sources.

After taking this course, you’ll easily use packages like Numpy, Pandas, and Matplotlib to work with real data in Python..

You’ll even understand concepts like unsupervised learning, dimension reduction and supervised learning.. I will even introduce you to deep learning and neural networks using the powerful H2o framework!

Most importantly, you will learn to implement these techniques practically using Python. You will have access to all the data and scripts used in this course. Remember, I am always around to support my students!

JOIN MY COURSE NOW!

Who this course is for:

• Students Interested In Getting Started With Data Science Applications In The Python Environment
• People Wanting To Master The Anaconda iPython Environment For Data Science & Scientific Computations
• Students Wishing To Learn The Implementation Of Unsupervised Learning On Real Data Using Python
• Students Wishing To Learn The Implementation Of Supervised Learning (Classification) On Real Data Using Python
• Students Looking To Get Started With Artificial Neural Networks & Deep Learning

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Applied Statistical Modeling for Data Analysis in R

APPLIED STATISTICAL MODELING FOR DATA ANALYSIS IN R

COMPLETE GUIDE TO STATISTICAL DATA ANALYSIS & VISUALIZATION FOR PRACTICAL APPLICATIONS IN R

            Confounded by Confidence Intervals? Pondering Over p-values? Hankering Over Hypothesis Testing?

Hello, My name is Minerva Singh and I am an Oxford University MPhil (Geography and Environment) graduate. I recently finished a PhD at Cambridge University (Tropical Ecology and Conservation).

I have several years of experience in analyzing real life data from different sources using statistical modeling and producing publications for international peer reviewed journals. If you find statistics books & manuals too vague, expensive & not practical, then you’re going to love this course!

I created this course to take you by hand and teach you all the concepts, and take your statistical modeling from basic to an advanced level for practical data analysis.

With this course, I want to help you save time and learn what the arcane statistical concepts have to do with the actual analysis of data and the interpretation of the bespoke results. Frankly, this is the only one course you need to complete  in order to get a head start in practical statistical modeling for data analysis using R.

My course has 9.5 hours of lectures and provides a robust foundation to carry out PRACTICAL, real-life statistical data analysis tasks in R, one of the most popular and FREE data analysis frameworks.

GET ACCESS TO A COURSE THAT IS JAM PACKED WITH TONS OF APPLICABLE INFORMATION! AND GET A FREE VIDEO COURSE IN MACHINE LEARNING AS WELL!

This course is your sure-fire way of acquiring the knowledge and statistical data analysis skills that I acquired from the rigorous training I received at 2 of the best universities in the world, perusal of numerous books and publishing statistically rich papers in renowned international journal like PLOS One.

To be more specific, here’s what the course will do for you:

 (a) It will take you (even if you have no prior statistical modelling/analysis background) from a basic level to performing some of the most common advanced statistical data analysis tasks in R.

 (b) It will equip you to use R for performing the different statistical data analysis and visualization tasks for data modelling.

 © It will Introduce some of the most important statistical concepts to you in a practical manner such that you can apply these concepts for practical data analysis and interpretation.

 (d) You will learn some of the most important statistical modelling concepts from probability distributions to hypothesis testing to regression modelling and multivariate analysis.

 (e) You will also be able to decide which statistical modelling techniques are best suited to answer your research questions and applicable to your data and interpret the results.

The course will mostly focus on helping you implement different statistical analysis techniques on your data and interpret the results.

After each video you will learn a new concept or technique which you may apply to your own projects immediately!

TAKE ACTION NOW :) You’ll also have my continuous support when you take this course just to make sure you’re successful with it.  If my GUARANTEE is not enough for you, you can ask for a refund within 30 days of your purchase in case you’re not completely satisfied with the course.

TAKE ACTION TODAY! I will personally support you and ensure your experience with this course is a success.

Who this course is for:

• People working in any numerate field which requires data analysis
• Students of Environmental Science, Ecology, Biology,Conservation and Other Natural Sciences
• People with some prior knowledge of the R interface- (a) installing packages (b) reading in csv files
• People carrying out observational or experimental studies

#Applied #Statistical Modeling for #Data #Analysis in R !!! 85% off!! #umedy #course #couponcode
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Applied Statistical Modeling for Data Analysis in R

Applied Statistical Modeling for Data Analysis in R

Satellite Remote Sensing Data Bootcamp With Opensource Tools

ENROLL IN MY LATEST COURSE ON HOW TO LEARN ALL ABOUT BASIC SATELLITE REMOTE SENSING.

Are you currently enrolled in either of my Core or Intermediate Spatial Data Analysis Courses?

Or perhaps you have prior experience in GIS or tools like R and QGIS?

You don’t want to spend 100s and 1000s of dollars on buying commercial software for imagery analysis?

The next step for you is to gain profIciency in satellite remote sensing data analysis.

MY COURSE IS A HANDS ON TRAINING WITH REAL REMOTE SENSING DATA WITH OPEN SOURCE TOOLS!

My course provides a foundation to carry out PRACTICAL, real-life remote sensing analysis tasks in popular and FREE software frameworks with REAL spatial data. By taking this course, you are taking an important step forward in your GIS journey to become an expert in geospatial analysis.

Why Should You Take My Course?

I am an Oxford University MPhil (Geography and Environment) graduate. I also completed a PhD at Cambridge University (Tropical Ecology and Conservation).

I have several years of experience in analyzing real life spatial remote sensing data from different sources and producing publications for international peer reviewed journals.

In this course, actual satellite remote sensing data such as Landsat from USGS and radar data from JAXA  will be used to give a practical hands-on experience of working with remote sensing and understanding what kind of questions remote  sensing can help us answer.

This course will ensure you learn & put remote sensing data analysis into practice today and increase your proficiency in geospatial analysis.

Remote sensing software tools are very expensive and their cost can run into thousands of dollars. Instead of shelling out so much money or procuring pirated copies (which puts you at a risk of prosecution), you will learn to carry out some of the most important and common remote sensing analysis tasks using a number of popular, open source GIS tools such as R, QGIS, GRASS and ESA-SNAP.  All of which are in great demand in the geospatial sector and improving your skills in these is a plus for you.

This is an introductory course, i.e. we will focus on learning the most important and widely encountered remote sensing data processing and analyzing tasks in R, QGIS, GRASS and ESA-SNAP

You will also learn about the different sources of remote sensing data there are and how to obtain these FREE OF CHARGE and process them using FREE SOFTWARE.

In addition to all the above, you’ll have MY CONTINUOUS SUPPORT to make sure you get the most value out of your investment!

ENROLL NOW :)

Who this course is for:

• People with prior expereince of working spatial data
• GIS analysts
• Ecologists
• Forestry and Conservation Practioners
• Geographers
• Geologists

92% off #udemy course #couponcode
#Satellite #Remote Sensing Data #Bootcamp With #Opensource Tools
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Satellite Remote Sensing Data Bootcamp With Opensource Tools

Satellite Remote Sensing Data Bootcamp With Opensource Tools

ArcGIS Desktop For Spatial Analysis: Go From Basic To Pro

I WANNA LEARN SPATIAL DATA ANALYSIS, BUT…

I found most spatial data books & manuals vague

There are no courses that actually teach me how it’s actually done

Available resources are expensive & I can’t afford them

I want to get a job in the field of GIS and geospatial analysis

I work in the field of ecology or quantitative social sciences or hydrology or civil engineering or geography

If you found yourself in one of these situations, then..

I’VE GOT GREAT NEWS FOR YOU!

Over the past few months, I have published multiple courses on Udemy around this topic which will be tremendously helpful to you & most important of all AFFORDABLE!

Today, I’ve created yet another powerful resource for you!

In this course, over 50+ hands-on and practical lecture, I will help you master the most common and important geo-processing tasks that can be performed with ArcGIS Desktop, one of THE MOST important GIS software tools available.

I will also show you the kind of questions answered through Spatial Analysis & data used.

THE STEPS I’LL WALK YOU THROUGH:

First of all, we’ll start some basic GIS tasks like “Zooming”.

Then, we’ll move into more complex processing tasks like “Geo-Statistics”.

We’ll also deal with some theoretical concepts related to Spatial Data Analysis, and then we’ll focus on implementing some of the most common GIS techniques (all the way showing you how to execute these tasks in ArcGIS Desktop).

The stuff you’ll learn from this course will be extremely useful in terms of you being able to implement it on future Spatial Data projects you’ll be working on (in a variety of disciplines from ecology to engineering).

LEARN FROM AN ACTUAL EXPERT IN THIS AREA:

My name is MINERVA SINGH.

I am an Oxford University MPhil (Geography and Environment) graduate.

I recently finished my PhD at Cambridge University (Tropical Ecology and Conservation).

I have SEVERAL YEARS OF EXPERIENCE in analyzing REAL LIFE DATA from different sources in ArcGIS Desktop.

I’ve also published my work in many international peer reviewed journals.

HERE IS HOW MY COURSE IS UNIQUE..

My course is a HANDS ON TRAINING with REAL data.

It’s a step by step course covering both the THEORY & APPLICATION of Spatial Data Analysis.

I teach Practical Stuff that you can learn quickly and start implementing NOW.

This is one of the most comprehensive courses on this topic.

I advise you to take advantage of it & enroll in the course TODAY!

TAKE ACTION TODAY! I will personally support you and ensure your experience with this course is a success. I answer all questions put to me and guide my students when they get stuck.

Please make sure you have access to ArcGIS before enrolling

Who this course is for:

• Academics and Researchers
• Conservation managers, field ecologists and social scientists
• People looking to get started in the field of GIS Analysis
• Students of Geography, Environmental Sciences, Geology, Hydrology, Engineering, Earth Sciences and Ecology
• People looking to use ArcGIS Desktop in academic or professional settings

#ArcGIS #Desktop For Spatial #Analysis: Go From Basic To #Pro 90% off !!! #coupon #offer #discount #deals #couponcode
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