Data and Visual Analytics is a growing field that specialises in analysing, modelling, and visualising complex high dimensional data.

You will learn to handle complex real-world data. The course illustrates several case studies and hands-on work with the R programming language. At first, you will learn how to work on R programming software. Then the course shows you the process of data analysis covering Data Preprocessing, Data Processing and Data Visualization.

Finally, the course covers Regression including Logistic Regression, Linear Regression, and Regularization.

**Assessment**

This course does not involve any written exams. Students need to answer 5 assignment questions to complete the course, the answers will be in the form of written work in pdf or word. Students can write the answers in their own time. Each answer needs to be 200 words (1 Page). Once the answers are submitted, the tutor will check and assess the work.

**Certification**

Edukite courses are free to study. To successfully complete a course you must submit all the assignment of the course as part of the assessment. Upon successful completion of a course, you can choose to make your achievement formal by obtaining your Certificate at a cost of £49.

Having an Official Edukite Certification is a great way to celebrate and share your success. You can:

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- Show it to prove your success

Course Credit: Georgia Institute of Technology

### Course Curriculum

Module: 1 | |||

Data is Ubiquitous – Data Analysis with R 1 | 00:02:00 | ||

Data is Ubiquitous – Data Analysis with R 2 | 00:01:00 | ||

Go Exploring – Data Analysis with R 3 | 00:01:00 | ||

Why learn EDA? – Data Analysis with R 4 | 00:03:00 | ||

Aude’s Interest in Data – Data Analysis with R 5 | 00:01:00 | ||

Goals of EDA – Data Analysis with R 6 | 00:02:00 | ||

The Growth of Televisions – Data Analysis with R 7 | 00:01:00 | ||

The Growth of Televisions – Data Analysis with R 8 | 00:02:00 | ||

Our Approach for This Course – Data Analysis with R 9 | 00:01:00 | ||

Aude Explores Coordinated Migration – Data Analysis with R 10 | 00:03:00 | ||

Module: 2 | |||

Course Overview – Data Analysis with R 11 | 00:01:00 | ||

The Power of R – Data Analysis with R 12 | 00:01:00 | ||

The Power of R – Data Analysis with R 13 | 00:01:00 | ||

Why R – Data Analysis with R 14 | 00:01:00 | ||

Install RStudio on Windows – Data Analysis with R 15 | 00:02:00 | ||

Install RStudio on a Mac – Data Analysis with R 16 | 00:01:00 | ||

RStudio Layout – Data Analysis with R 17 | 00:02:00 | ||

RStudio Layout – Data Analysis with R 18 | 00:01:00 | ||

Demystifying R – Data Analysis with R 19 | 00:02:00 | ||

Demystifying R – Data Analysis with R 20 | 00:01:00 | ||

Module: 3 | |||

Getting Help – Data Analysis with R 21 | 00:01:00 | ||

Read and Subset Data – Data Analysis with R 22 | 00:04:00 | ||

R Markdown Documents – Data Analysis with R 23 | 00:02:00 | ||

R Markdown Documents – Data Analysis with R 24 | 00:01:00 | ||

Factor Variables – Data Analysis with R 25 | 00:02:00 | ||

Ordered Factors – Data Analysis with R 26 | 00:02:00 | ||

Ordered Factors – Data Analysis with R 27 | 00:01:00 | ||

Setting Levels of Ordered Factors – Data Analysis with R 28 | 00:01:00 | ||

Setting Levels of Ordered Factors – Data Analysis with R 29 | 00:01:00 | ||

Data Munging – Data Analysis with R 30 | 00:01:00 | ||

Module: 4 | |||

Advice for Data Scientists – Data Analysis with R 31 | 00:01:00 | ||

Congratulations – Data Analysis with R 32 | 00:01:00 | ||

Welcome! – Data Analysis with R 33 | 00:01:00 | ||

What to Do First? – Data Analysis with R 34 | 00:01:00 | ||

Pseudo-Facebook User Data – Data Analysis with R 35 | 00:02:00 | ||

Histogram of Users’ Birthdays – Data Analysis with R 36 | 00:02:00 | ||

Histogram of Users’ Birthdays – Data Analysis with R 37 | 00:01:00 | ||

Moira’s Investigation – Data Analysis with R 38 | 00:01:00 | ||

Estimating Your Audience Size – Data Analysis with R 39 | 00:01:00 | ||

Perceived Audience Size – Data Analysis with R 40 | 00:01:00 | ||

Module: 5 | |||

Faceting – Data Analysis with R 41 | 00:02:00 | ||

Faceting – Data Analysis with R 42 | 00:01:00 | ||

Be Skeptical Outliers and Anomalies – Data Analysis with R 43 | 00:02:00 | ||

Moira’s Outlier – Data Analysis with R 44 | 00:01:00 | ||

Moira’s Outlier – Data Analysis with R 45 | 00:01:00 | ||

Friend Count – Data Analysis with R 46 | 00:01:00 | ||

Friend Count – Data Analysis with R 47 | 00:01:00 | ||

Limiting the Axes – Data Analysis with R 48 | 00:01:00 | ||

Exploring with Bin Width – Data Analysis with R 49 | 00:01:00 | ||

Adjusting the Bin Width – Data Analysis with R 50 | 00:01:00 | ||

Module: 6 | |||

Faceting Friend Count – Data Analysis with R 51 | 00:01:00 | ||

Omitting NA Observations – Data Analysis with R 52 | 00:01:00 | ||

Statistics ‘by’ Gender – Data Analysis with R 53 | 00:01:00 | ||

Statistics ‘by’ Gender – Data Analysis with R 54 | 00:01:00 | ||

Labeling Plots – Data Analysis with R 55 | 00:01:00 | ||

Tenure Histogram By Years – Data Analysis with R 56 | 00:01:00 | ||

Labeling Plots – Data Analysis with R 57 | 00:01:00 | ||

User Ages – Data Analysis with R 58 | 00:01:00 | ||

User Ages – Data Analysis with R 59 | 00:02:00 | ||

The Spread of Memes – Data Analysis with R 60 | 00:01:00 | ||

Module: 7 | |||

Lada’s Money Bag Meme – Data Analysis with R 61 | 00:03:00 | ||

Transforming Data – Data Analysis with R 62 | 00:03:00 | ||

Transforming Data – Data Analysis with R 63 | 00:03:00 | ||

Add a Scaling Layer – Data Analysis with R 64 | 00:01:00 | ||

Frequency Polygons – Data Analysis with R 65 | 00:03:00 | ||

Frequency Polygons – Data Analysis with R 66 | 00:01:00 | ||

Likes on the Web – Data Analysis with R 67 | 00:01:00 | ||

Likes on the Web – Data Analysis with R 68 | 00:01:00 | ||

Box Plots – Data Analysis with R 69 | 00:02:00 | ||

Box Plots – Data Analysis with R 70 | 00:01:00 | ||

Module: 8 | |||

“Box Plots 71 | 00:02:00 | ||

“Box Plots 72 | 00:02:00 | ||

Getting Logical – Data Analysis with R 73 | 00:02:00 | ||

Getting Logical – Data Analysis with R 74 | 00:01:00 | ||

Analyzing One Variable – Data Analysis with R 75 | 00:01:00 | ||

Analyzing One Variable – Data Analysis with R 76 | 00:01:00 | ||

Welcome! – Data Analysis with R 77 | 00:01:00 | ||

Scatterplots and Perceived Audience Size – Data Analysis with R 78 | 00:01:00 | ||

Scatterplots – Data Analysis with R 79 | 00:01:00 | ||

Scatterplots – Data Analysis with R 80 | 00:01:00 | ||

Module: 9 | |||

ggplot Syntax – Data Analysis with R 81 | 00:02:00 | ||

Overplotting – Data Analysis with R 82 | 00:01:00 | ||

Overplotting – Data Analysis with R 83 | 00:01:00 | ||

coord_trans() – Data Analysis with R 84 | 00:01:00 | ||

coord_trans() – Data Analysis with R 85 | 00:01:00 | ||

Alpha and Jitter – Data Analysis with R 86 | 00:01:00 | ||

Alpha and Jitter – Data Analysis with R 87 | 00:02:00 | ||

Overplotting and Domain Knowledge – Data Analysis with R 88 | 00:02:00 | ||

Conditional Means – Data Analysis with R 89 | 00:05:00 | ||

Conditional Means – Data Analysis with R 90 | 00:01:00 | ||

Module: 10 | |||

Overlaying Summaries with Raw Data – Data Analysis with R 91 | 00:03:00 | ||

Overlaying Summaries Solution – Data Analysis with R 92 | 00:01:00 | ||

Moira: Histogram Summary & Scatterplots – Data Analysis with R 93 | 00:02:00 | ||

Correlation – Data Analysis with R 94 | 00:01:00 | ||

Correlation – Data Analysis with R 95 | 00:01:00 | ||

Correlation on Subsets – Data Analysis with R 96 | 00:01:00 | ||

Correlation on Subsets – Data Analysis with R 97 | 00:01:00 | ||

Correlation Methods – Data Analysis with R 98 | 00:01:00 | ||

Create Scatterplots – Data Analysis with R 99 | 00:01:00 | ||

Create Scatterplots – Data Analysis with R 100 | 00:01:00 | ||

Module: 11 | |||

Strong Correlations – Data Analysis with R 101 | 00:01:00 | ||

Strong Correlations – Data Analysis with R102 | 00:01:00 | ||

Moira on Correlation – Data Analysis with R 103 | 00:01:00 | ||

More Caution with Correlation – Data Analysis with R 104 | 00:01:00 | ||

More Caution with Correlation – Data Analysis with R 105 | 00:01:00 | ||

Noisy Scatterplots – Data Analysis with R 106 | 00:01:00 | ||

Noisy Scatterplots – Data Analysis with R 107 | 00:01:00 | ||

Making Sense of Data – Data Analysis with R 108 | 00:01:00 | ||

Making Sense of Data – Data Analysis with R 109 | 00:01:00 | ||

A New Perspective – Data Analysis with R 110 | 00:01:00 | ||

Module: 12 | |||

A New Perspective – Data Analysis with R 111 | 00:01:00 | ||

Understanding Noise: Age to Age Months – Data Analysis with R 112 | 00:02:00 | ||

Understanding Noise: Age to Age Months – Data Analysis with R 113 | 00:01:00 | ||

Age with Months Means – Data Analysis with R 114 | 00:01:00 | ||

Age with Months Means – Data Analysis with R 115 | 00:03:00 | ||

Noise in Conditional Means – Data Analysis with R 116 | 00:01:00 | ||

Noise in Conditional Means – Data Analysis with R 117 | 00:01:00 | ||

Smoothing Conditional Means – Data Analysis with R 118 | 00:03:00 | ||

Which Plot to Choose? – Data Analysis with R 119 | 00:01:00 | ||

Analyzing Two Variables – Data Analysis with R 120 | 00:01:00 | ||

Module: 13 | |||

Analyzing Two Variables – Data Analysis with R 121 | 00:01:00 | ||

Multivariate Data – Data Analysis with R 122 | 00:01:00 | ||

Perceived Audience Size by Age – Data Analysis with R 123 | 00:01:00 | ||

Third Qualitative Variable – Data Analysis with R 124 | 00:02:00 | ||

Third Qualitative Variable – Data Analysis with R 125 | 00:01:00 | ||

Plotting Conditional Summaries – Data Analysis with R 126 | 00:01:00 | ||

Plotting Conditional Summaries – Data Analysis with R 127 | 00:01:00 | ||

Thinking in Ratios – Data Analysis with R 128 | 00:01:00 | ||

Wide and Long Format – Data Analysis with R 129 | 00:01:00 | ||

Reshaping Data – Data Analysis with R 130 | 00:02:00 | ||

Module: 14 | |||

Ratio Plot – Data Analysis with R 131 | 00:01:00 | ||

Ratio Plot – Data Analysis with R 132 | 00:01:00 | ||

Third Quantitative Variable – Data Analysis with R 133 | 00:01:00 | ||

Third Quantitative Variable – Data Analysis with R 134 | 00:01:00 | ||

Cut a Variable – Data Analysis with R 135 | 00:01:00 | ||

Cut a Variable – Data Analysis with R 136 | 00:01:00 | ||

Plotting It All Together – Data Analysis with R 137 | 00:01:00 | ||

Plotting It All Together – Data Analysis with R 138 | 00:01:00 | ||

Plot the Grand Mean – Data Analysis with R 139 | 00:01:00 | ||

Plot the Grand Mean – Data Analysis with R 140 | 00:01:00 | ||

Module: 15 | |||

Friending Rate – Data Analysis with R 141 | 00:01:00 | ||

Friending Rate – Data Analysis with R 142 | 00:01:00 | ||

Friendships Initiated – Data Analysis with R 143 | 00:01:00 | ||

Friendships Initiated – Data Analysis with R 144 | 00:01:00 | ||

Bias Variance Trade off Revisited – Data Analysis with R 145 | 00:01:00 | ||

Bias Variance Trade off Revisited – Data Analysis with R 146 | 00:01:00 | ||

Sean’s NFL Fan Sentiment Study – Data Analysis with R 147 | 00:01:00 | ||

Introducing the Yogurt Dataset – Data Analysis with R 148 | 00:02:00 | ||

Histograms Revisited – Data Analysis with R 149 | 00:01:00 | ||

Histograms Revisited – Data Analysis with R 150 | 00:01:00 | ||

Module: 16 | |||

Number of Purchases – Data Analysis with R 151 | 00:01:00 | ||

Number of Purchases – Data Analysis with R 152 | 00:01:00 | ||

Prices Over Time – Data Analysis with R 153 | 00:01:00 | ||

Prices Over Time – Data Analysis with R 154 | 00:01:00 | ||

Sampling Observations – Data Analysis with R 155 | 00:01:00 | ||

Looking at Samples of Households – Data Analysis with R 156 | 00:02:00 | ||

The Limits of Cross Sectional Data – Data Analysis with R 157 | 00:01:00 | ||

Many Variables – Data Analysis with R 158 | 00:02:00 | ||

Scatterplot Matrices – Data Analysis with R 159 | 00:02:00 | ||

Scatterplot Matrices – Data Analysis with R 160 | 00:01:00 | ||

Module: 17 | |||

Even More Variables – Data Analysis with R 161 | 00:01:00 | ||

Heat Maps – Data Analysis with R 162 | 00:02:00 | ||

Analyzing Three or More Variables – Data Analysis with R 163 | 00:01:00 | ||

Analyzing Three or More Variables – Data Analysis with R 164 | 00:01:00 | ||

Welcome! – Data Analysis with R 165 | 00:01:00 | ||

Scatterplot Review – Data Analysis with R 166 | 00:01:00 | ||

Scatterplot Review – Data Analysis with R 167 | 00:01:00 | ||

Price and Carat Relationship – Data Analysis with R 168 | 00:01:00 | ||

Price and Carat Relationship – Data Analysis with R 169 | 00:01:00 | ||

Frances Gerety – Data Analysis with R 170 | 00:02:00 | ||

Module: 18 | |||

Frances Gerety – Data Analysis with R 171 | 00:01:00 | ||

The Rise of Diamonds – Data Analysis with R 172 | 00:01:00 | ||

ggpairs Function – Data Analysis with R 173 | 00:01:00 | ||

ggpairs Function – Data Analysis with R 174 | 00:01:00 | ||

The Demand of Diamonds – Data Analysis with R 175 | 00:01:00 | ||

The Demand of Diamonds – Data Analysis with R 176 | 00:01:00 | ||

Connecting Demand and Price Distribution – Data Analysis with R 177 | 00:01:00 | ||

Connecting Demand and Price Distribution – Data Analysis with R 178 | 00:01:00 | ||

Scatterplot Transformation – Data Analysis with R 179 | 00:01:00 | ||

Overplotting Revisited – Data Analysis with R 180 | 00:01:00 | ||

Module: 19 | |||

Overplotting Revisited – Data Analysis with R 181 | 00:01:00 | ||

Plot Colors for Qualitative Factors – Data Analysis with R 182 | 00:01:00 | ||

Price vs. Carat and Clarity – Data Analysis with R 183 | 00:01:00 | ||

Price vs. Carat and Clarity – Data Analysis with R 184 | 00:01:00 | ||

Clarity and Price – Data Analysis with R 185 | 00:01:00 | ||

Clarity and Price – Data Analysis with R 186 | 00:01:00 | ||

Price vs Carat and Cut – Data Analysis with R 187 | 00:01:00 | ||

Price vs Carat and Cut – Data Analysis with R 188 | 00:01:00 | ||

Cut and Price – Data Analysis with R 189 | 00:01:00 | ||

Cut and Price – Data Analysis with R 190 | 00:01:00 | ||

Module: 20 | |||

Price vs Carat and Color – Data Analysis with R 191 | 00:01:00 | ||

Price vs Carat and Color – Data Analysis with R 192 | 00:01:00 | ||

Color and Price – Data Analysis with R 193 | 00:01:00 | ||

Color and Price – Data Analysis with R 194 | 00:01:00 | ||

Linear Models in R – Data Analysis with R 195 | 00:01:00 | ||

Linear Models in R – Data Analysis with R 196 | 00:01:00 | ||

Building the Linear Model – Data Analysis with R 197 | 00:01:00 | ||

Model Problems – Data Analysis with R 198 | 00:01:00 | ||

Model Problems – Data Analysis with R 199 | 00:01:00 | ||

“A Bigger 200 | 00:01:00 | ||

Assessment | |||

Submit Your Assignment | 00:00:00 | ||

Certification | 00:00:00 |

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