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The Introduction to Data Science class will survey the foundational topics in data science, namely: Data Manipulation, Data Analysis with Statistics and Machine Learning, Data Communication with Information Visualization, Data at Scale — Working with Big Data. The class will focus on breadth and present the topics briefly instead of focusing on a single topic in depth and apply the basic techniques of data science.

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.

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Course Credit: Udacity

Course Curriculum

Module: 01
1 Introduction to Data Science – Intro to Data Science 00:01:00
2 What Is a Data Scientist? – Intro to Data Science 00:01:00
3 What Is a Data Scientist? – Intro to Data Science 00:01:00
4 What Is a Data Scientist? – Intro to Data Science 00:01:00
5 What Does a Data Scientist Do? – Intro to Data Science 00:01:00
6 Pi Chuan – Introduction – Intro to Data Science 00:01:00
7 Pi Chuan – O que é ciência de dados? 00:01:00
8 Gabor – Introduction – Intro to Data Science 00:01:00
9 Gabor – What Is Data Science? – Intro to Data Science 00:01:00
10 Basic Data Scientist Skills – Intro to Data Science 00:01:00
Module: 02
11 Habilidades básicas de um cientista de dados 00:01:00
12 Habilidades básicas de um cientista de dados 00:01:00
Problems Solved by Data Science – Intro to Data Science 00:03:00
14 Intro to Numpy and Pandas – Intro to Data Science 00:01:00
15 Numpy – Intro to Data Science 00:01:00
16 Pandas – Intro to Data Science 00:02:00
Dataframe — Average Gold Medal – Intro to Data Science 00:01:00
18 Dataframe — Average Gold Medal – Intro to Data Science 00:01:00
19 Dataframe Columns – Intro to Data Science 00:02:00
21 Pandas Vectorized Methods – Intro to Data Science 00:01:00
Module: 03
22 Average Bronze Medals – Intro to Data Science 00:01:00
23 Average Bronze Medals – Intro to Data Science 00:01:00
24 “Average Gold 00:01:00
24 “Average Gold 00:01:00
25 Multiplicação de matrizes e Numpy 00:02:00
26 Olympics Medal Points – Intro to Data Science 00:01:00
27 Olympics Medal Points – Intro to Data Science 00:01:00
28 Pandas – Intro to Data Science 00:01:00
29 Dataframes – Intro to Data Science 00:01:00
30 Create a New Dataframe – Intro to Data Science 00:02:00
Module: 04
31 Lesson Project – Titanic Data – Intro to Data Science 00:01:00
32 Class Project – Intro to Data Science 00:01:00
33 Advice for Aspiring Students – Intro to Data Science 00:01:00
34 Advice for Aspiring Data Scientists – Intro to Data Science 00:01:00
35 Recap of Lesson 1 – Intro to Data Science 00:01:00
84 Bem-vindo à Aula 2 00:01:00
37 Nick – Introdução 00:01:00
38 O que é Data Wrangling? 00:01:00
39 Analisando Dados Bagunçados 1 00:01:00
40 Analisando Dados Bagunçados 2 00:01:00
Module: 05
41 Experiência do Nick com Data Wrangling 00:01:00
42 Obtendo dados 00:01:00
43 Formatos comuns de dados 00:03:00
44 Dados CSV 1 00:01:00
45 Dados CSV 2 00:01:00
46 CSV Exercise – Intro to Data Science 00:01:00
47 CSV Exercise – Intro to Data Science 00:01:00
48 Quais são os bancos de dados relacionais? 00:01:00
49 Dados de Aadhaar 00:01:00
50 Relational Databases – Intro to Data Science 00:01:00
Module: 06
51 Relational Databases – Intro to Data Science 00:02:00
52 Dados Aadhaar e bancos de dados 00:01:00
53 Introdução aos esquemas dos banco de dados 00:01:00
54 Database Schema – Intro to Data Science 00:01:00
55 Database Schema – Intro to Data Science 00:01:00
56 Consultas Simples 00:02:00
57 Write Your Own Simple Query – Intro to Data Science 00:01:00
58 Write Your Own Simple Query – Intro to Data Science 00:01:00
59 Consultas complexas 1 00:01:00
60 Consultas complexas 2 00:03:00
Module: 07
61 Write Your Own Complex Query – Intro to Data Science 00:01:00
62 Write Your Own Complex Query – Intro to Data Science 00:01:00
63 APIs 00:01:00
64 Exemplo de API 00:01:00
65 Dados no formato JSON 00:01:00
66 Como acessar uma API de forma eficiente 00:02:00
67 API Exercise – Intro to Data Science 00:01:00
68 API Exercise – Intro to Data Science 00:01:00
69 Sanity Checking Data 00:01:00
70 Função describe de Pandas 00:02:00
Module: 08
71 Why Are Values Missing? – Intro to Data Science 00:01:00
72 Why Are Values Missing? – Intro to Data Science 00:01:00
73 Valores perdidos 00:02:00
74 Lidando com dados perdidos 00:02:00
75 Porque fazer imputação 00:01:00
76 Imputação fácil 00:01:00
77 Fazer imputação usando Regressão Linear 00:01:00
78 Imputation Exercise – Intro to Data Science 00:01:00
79 Imputation Exercise – Intro to Data Science 00:01:00
80 Imputação é apenas a ponta do iceberg 00:01:00
Module: 09
81 Tarefa 2 00:01:00
82 O projeto mais legal do Nick 00:01:00
83 Recapitulação 00:01:00
84 Bem-vindo à Aula 2 00:01:00
85 Statistical Rigor Part 1 – Intro to Data Science 00:01:00
86 Statistical Rigor Part 2 – Intro to Data Science 00:01:00
87 Introdução de Kurt 00:01:00
88 Why Is Statistics Useful? – Intro to Data Science 00:01:00
89 Statistical Rigor Exercise – Intro to Data Science 00:01:00
90 Statistical Rigor Exercise – Intro to Data Science 00:01:00
Module: 10
91 Statistical Test – Intro to Data Science 00:01:00
92 Statistical Test – Intro to Data Science 00:01:00
93 Introduction to Normal Distribution – Intro to Data Science 00:01:00
94 Normal Distribution – Intro to Data Science 00:01:00
95 Normal Distribution – Intro to Data Science 00:01:00
96 t-Test – Intro to Data Science 00:01:00
97 Welch’s Two-Sample t-Test – Intro to Data Science 00:03:00
98 Welch’s t-Test in Python – Intro to Data Science 00:01:00
99 Welch’s t-Test in Python – Intro to Data Science 00:01:00
100 Welch’s t-Test Exercise – Intro to Data Science 00:01:00
Module: 11
101 Welch’s t-Test Exercise – Intro to Data Science 00:01:00
102 Non-Parametric Test – Intro to Data Science 00:02:00
103 Non-Normal Data – Intro to Data Science 00:02:00
104 Definition of Non-Parametric Test – Intro to Data Science 00:01:00
105 Definition of Non-Parametric Test – Intro to Data Science 00:01:00
106 Just the Tip of the Iceberg – Intro to Data Science 00:01:00
107 Predicting Future Data – Intro to Data Science 00:01:00
108 O que é a Machine Learning? 00:01:00
109 Por que machine learning é útil? 00:01:00
110 Estatística vs. Machine Learning 00:01:00
Module: 12
111 Diferentes tipos de aprendizagem 00:02:00
112 O algoritmo de ML favorito de Kurt 00:01:00
113 Previsão com regressão 00:01:00
114 Regressão linear com gradiente descendente 00:03:00
115 Batting Average with Linear Regression – Intro to Data Science 00:01:00
116 Batting Average with Linear Regression – Intro to Data Science 00:01:00
117 Cost Function – Intro to Data Science 00:02:00
118 How to Minimize Cost Function – Intro to Data Science 00:03:00
119 Gradient Descent in Python – Intro to Data Science 00:01:00
120 Gradient Descent in Python – Intro to Data Science 00:02:00
Module: 13
121 Coeficientes de Determinação 00:01:00
122 Calculating R^2 – Intro to Data Science 00:01:00
123 Calculating R^2 – Intro to Data Science 00:01:00
124 Outras Considerações 00:03:00
125 O conselho de Kurt para boas práticas de ML 00:02:00
126 Conselhos para aspirantes a Cientistas de Dados 00:02:00
127 Tarefa 2 00:01:00
128 Aula 3 Recapitulação 00:01:00
129 Welcome to Lesson 4 – Intro to Data Science 00:01:00
130 Effective Information Visualization – Intro to Data Science 00:01:00
Module: 14
131 Napoleon’s Ill-Fated March to Russia – Intro to Data Science 00:01:00
132 What Do You See in This Visualization? – Intro to Data Science 00:01:00
133 What Do You See in This Visualization? – Intro to Data Science 00:01:00
134 What Makes a Visualization Effective? – Intro to Data Science 00:01:00
135 What Makes a Visualization Effective? – Intro to Data Science 00:03:00
136 Introducing Don – Intro to Data Science 00:01:00
137 Don’s Advice on Communicating Findings – Intro to Data Science 00:01:00
138 Introducing Rishiraj – Intro to Data Science 00:01:00
139 Rishi on Communicating Findings Well – Intro to Data Science 00:01:00
140 Visual Encodings Part 1 – Intro to Data Science 00:02:00
Module: 15
141 Visual Encodings Part 2 – Intro to Data Science 00:01:00
142 Visual Encodings Part 3 – Intro to Data Science 00:02:00
143 Visual Encoding Lecture – Intro to Data Science 00:01:00
144 Visual Encoding Solution – Intro to Data Science 00:01:00
145 Perception of Visual Cues – Intro to Data Science 00:02:00
146 Plotting in Python – Intro to Data Science 00:04:00
147 Plotting in Python – Intro to Data Science 00:01:00
148 Plotting in Python – Intro to Data Science 00:01:00
149 Different Data Types 1 – Numeric Data – Intro to Data Science 00:02:00
150 Different Data Types 2 – Categorical Data – Intro to Data Science 00:01:00
Module: 16
151 Different Data Types 3 – Time Series Data – Intro to Data Science 00:01:00
152 Data Scales – Intro to Data Science 00:01:00
153 Improper Use of Scales – Intro to Data Science 00:01:00
154 Improper Use of Scales – Intro to Data Science 00:01:00
155 Plotting Line Charts – Intro to Data Science 00:01:00
156 Plotting Line Charts – Intro to Data Science 00:01:00
157 Visualizing Time Series Data – Intro to Data Science 00:01:00
158 Scatter Plots – Intro to Data Science 00:01:00
159 Line Charts – Intro to Data Science 00:01:00
160 LOESS Curves – Intro to Data Science 00:01:00
Module: 17
161 Multivariate Data Part 1 – Intro to Data Science 00:01:00
162 Multivariate Data Part 2 – Intro to Data Science 00:01:00
163 Rishraj’s Advice to You – Intro to Data Science 00:01:00
164 Don’s Advice to You – Intro to Data Science 00:02:00
165 Lesson 4 Recap – Intro to Data Science 00:01:00
166 Lesson 4 Conclusion – Intro to Data Science 00:01:00
167 Welcome to Lesson 5 – Intro to Data Science 00:01:00
168 Big Data and MapReduce – Intro to Data Science 00:02:00
169 Scenarios for MapReduce – Intro to Data Science 00:01:00
170 Scenarios for MapReduce – Intro to Data Science 00:01:00
Module: 18
171 Basics of MapReduce – Intro to Data Science 00:01:00
172 Counting Words Serially – Intro to Data Science 00:02:00
173 Counting Words Serially – Intro to Data Science 00:01:00
174 Counting Words in MapReduce – Part 1 – Intro to Data Science 00:01:00
175 Counting Words in MapReduce – Part 2 – Intro to Data Science 00:01:00
176 Mapper – Intro to Data Science 00:02:00
177 Reducer – Intro to Data Science 00:02:00
178 MapReduce with Aadhaar Data – Intro to Data Science 00:01:00
179 Mapper and Reducer with Aadhaar Data – Intro to Data Science 00:01:00
180 Mapper and Reducer with Aadhaar Data – Intro to Data Science 00:02:00
Module: 19
181 More Complex MapReduce – Intro to Data Science 00:01:00
182 MapReduce Ecosystem – Intro to Data Science 00:01:00
183 Introducing Joshua – Intro to Data Science 00:01:00
184 MapReduce Tools – Intro to Data Science 00:01:00
185 Pig – Intro to Data Science 00:01:00
186 Best Part About Being a Data Scientist – Intro to Data Science 00:01:00
187 MapReduce with Subway Data – Intro to Data Science 00:00:00
188 Lesson 5 Recap – Intro to Data Science 00:01:00
189 Project Description – Intro to Data Science 00:01:00
190 Accuracy of Naive Bayes – Intro to Machine Learning 00:01:00
191 Accuracy of Naive Bayes – Intro to Machine Learning 00:01:00
Assessment
Submit Your Assignment 00:00:00
Certification 00:00:00

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