Udemy - Complete Python & Data Science Course for Absolute Beginners

1. 001 Introduction.mp436.23MB
2. 002 Intro To Python.mp440.4MB
3. 003 Variables.mp4108.02MB
4. 004 Type Conversion Examples.mp463.79MB
5. 005 Operators.mp446.46MB
6. 006 Operators Examples.mp4126.57MB
7. 007 Collections.mp451.61MB
8. 008 Lists.mp473.31MB
9. 009 Multidimensional List Examples.mp447.68MB
10. 010 Tuples Examples.mp456.36MB
11. 011 Dictionaries Examples.mp490.91MB
12. 012 Ranges Examples.mp457.6MB
13. 013 Conditionals.mp446.77MB
14. 014 If Statement Examples.mp456.84MB
15. 015 If Statement Variants Examples.mp473.77MB
16. 016 Loops.mp449.95MB
17. 017 While Loops Examples.mp465.87MB
18. 018 For Loops Examples.mp472.16MB
19. 019 Functions.mp454.59MB
20. 020 Functions Examples.mp451.34MB
21. 021 Parameters And Return Values Examples.mp482.3MB
22. 022 Classes and Objects.mp478.5MB
23. 023 Classes Example.mp478.8MB
24. 024 Objects Examples.mp486.43MB
25. 025 Inheritance Examples.mp4133.38MB
26. 026 Static Members Example.mp483.23MB
27. 027 Summary and Outro.mp429.29MB
28. 029 00. Course Intro.mp435.01MB
29. 030 01. Intro To Pyplot.mp435.12MB
30. 031 02. Installing Matplotlib.mp435.71MB
31. 032 03. Basic Line Plot.mp458.3MB
32. 033 04. Customizing Graphs.mp485.06MB
33. 034 05. Plotting Multiple Datasets.mp470.29MB
34. 035 06. Bar Chart.mp446.01MB
35. 036 07. Pie Chart.mp461.22MB
36. 037 08. Histogram.mp465.01MB
37. 038 09. 3D Plotting.mp451.39MB
38. 039 10. Course Outro.mp426.5MB
39. 041 00. Panda Course Introduction.mp439.47MB
40. 042 01. Intro To Pandas.mp450.33MB
41. 043 02. Installing Pandas.mp435.62MB
42. 044 03. Creating Pandas Series.mp4123.1MB
43. 045 04. Date Ranges.mp463.5MB
44. 046 05. Getting Elements From Series.mp4102.44MB
45. 047 06. Getting Properties Of Series.mp470.72MB
46. 048 07. Modifying Series.mp4103.27MB
47. 049 08. Operations On Series.mp465.1MB
48. 050 09. Creating Pandas Dataframes.mp4140.11MB
49. 051 10. Getting Elements From Dataframes.mp4140.82MB
50. 052 11. Getting Properties From Dataframes.mp4111.67MB
51. 053 12. Dataframe Modification.mp4240.74MB
52. 054 13. Dataframe Operations.mp4119.06MB
53. 055 14 Dataframe Comparisons And Iteration.mp492.99MB
54. 056 15. Reading CSVs.mp479.86MB
55. 057 16.summary And Outro.mp432.62MB
56. 059 Introduction to Data Mining.mp478.62MB
57. 061 Data Wrangling Demystified.mp4576.29MB
58. 063 01. Cluster Analysis.mp4232.15MB
59. 064 02. Classification and Regression.mp4301.49MB
60. 065 03. Association and Correlation.mp4124.1MB
61. 066 04. Dimensionality Reduction.mp4271.85MB
62. 068 01. Apache Spark - An Overview Of The Framework.mp4227.92MB
63. 069 02. Spark Key Functions.mp4193.57MB
64. 070 03. Spark Machine Learning.mp491.07MB
65. 071 04. EXAMPLES - Using The Machine Learning Pipeline.mp472.51MB
66. 073 01. Text Mining.mp4160.72MB
67. 074 02. Network Mining.mp4106.57MB
68. 075 03. Matrix.mp467.34MB
69. 076 04. SQL.mp4127.47MB
70. 078 01 NLP Data Cleaning.mp476.73MB
71. 079 02. Count Vectorizer.mp477.95MB
72. 080 03. NLP Example with Spam.mp498.46MB
73. 081 04. Tweak Model with Spam Data.mp461.95MB
74. 082 05. Pipeline with Spam Data.mp449.69MB
75. 084 06. Conclusion and Challenge.mp460.68MB
76. 086 00 Project Preview.mp426.26MB
77. 087 01 What Is Apache Spark.mp413.46MB
78. 088 02 What Are Resilient Distributed Datasets.mp47.43MB
79. 089 03A What Is A Dataframe.mp48.63MB
80. 090 03B What You'll Need.mp48.64MB
81. 092 04 Start A Spark Session.mp423.55MB
82. 093 05 Load Data As A CSV.mp441.08MB
83. 094 06 Perform Basic Dataframe Operations.mp432.18MB
84. 095 07 Format Dataframe Table.mp438.95MB
85. 096 08 Perform Dataframe Math Operations.mp462.75MB
86. 097 09 Perform Dataframe Queries.mp487.99MB
87. 098 10 Build SQL Queries With Spark.mp444.19MB
88. 100 00 Project Preview.mp419.82MB
89. 101 01 Convert Csv File To A Python List.mp495.68MB
90. 102 02 Tokenize Text Data.mp4168.6MB
91. 103 03 Find Most Popular Lemmatized Words.mp492.61MB
92. 104 04 Build Dataframes Per Part Of Speech.mp434.01MB
93. 105 05 Plot Word Frequency.mp458.06MB
94. 107 00 Project Preview.mp416.89MB
95. 108 01 Load A Dataset.mp471.53MB
96. 109 02 Analyze The Main Feature.mp415.95MB
97. 110 03 Analyze Numerical Features.mp459.18MB
98. 111 04 Analyze Categorical Features.mp454.34MB
99. 113 01 Find Relationships Between Numerical Features.mp468.93MB
100. 114 02 Find Relationships Between Categorical Features.mp449.22MB
101. 115 03 Build Conditional Plots.mp448.51MB
102. 117 00 Course Overview.mp47.96MB
103. 118 01 What You'll Need.mp413.53MB
104. 120 01 Why You Must Know How To Work With Data.mp415.59MB
105. 122 01 How To Read An ER Model.mp413.99MB
106. 124 01 What Is A Database.mp421.56MB
107. 125 02 What Is A Relational Database.mp413.28MB
108. 127 01 How To Design Columns And Data Types.mp49.19MB
109. 128 02 Use Normal Forms To Check Your Design.mp427.01MB
110. 130 01 Build A SQLite Database With Python.mp434.35MB
111. 131 02 Add An Entry To The Table With SQL.mp433.01MB
112. 132 03 Add More Records To The Table.mp434.96MB
113. 133 04 Build A Second Table For Cross-Referencing.mp475.5MB
114. 134 05 Select Rows That Meet Conditions.mp446.88MB
115. 136 Course Overview.mp48.95MB
116. 137 01 Load And Create Data.mp466.55MB
117. 138 02 Perform Exploratory Data Analysis.mp427.24MB
118. 139 03 Visualize Data With Different Plots.mp457.55MB
119. 140 04 Analyze Features With More Plots.mp435.07MB
120. 141 05 Build Plots With Seaborn.mp435.42MB
121. 142 06 Build A Bokeh Plot.mp437.34MB
122. 143 07 Build A 3D Scatter Plot.mp420.07MB
123. 144 08 Rank Feature Importance.mp439.64MB
124. 145 09 Compare Positive And Negative Returns.mp435.48MB
125. 147 00 Project Preview.mp410.9MB
126. 148 01 Load Crypto Prices Dataset.mp459.82MB
127. 149 02 Visualize Bitcoin Price Trend.mp423.35MB
128. 150 03 Predict Price With Facebook Prophet.mp439.19MB
129. 151 04 Analyze Model Performance.mp474.87MB
130. 152 05 Visualize Model Results.mp426.64MB
131. 153 06 Predict Monthly Trend.mp462.1MB
132. 154 07 Predict Weekly Trend.mp436.9MB
133. 155 08 Compare Final Stock Price Of Different Strategies.mp442.98MB
134. 157 00 Project Preview.mp412.71MB
135. 158 01 Fetch Stock Data.mp457.59MB
136. 159 02 Visualize Stock Data Features.mp447.77MB
137. 160 03 Calculate Daily Return.mp424.09MB
138. 161 04 Compare Returns Of Different Stocks.mp473.48MB
139. 162 05 Compare Closing Prices.mp456.03MB
140. 164 01 Visualize Standard Deviation And Expected Returns.mp426.74MB
141. 165 02 Calculate Value At Risk.mp421.08MB
142. 166 03 Monte Carlo Analysis To Estimate Risk.mp452.01MB
143. 167 04 Visualize Price Distribution.mp460.41MB
144. 169 00 What Is Web Scraping.mp421.98MB
145. 170 01 What You'll Need.mp47.49MB
146. 172 02 Build An HTML Webpage To Scrape.mp484.26MB
147. 173 03 Select Data Structures From A Webpage.mp434.93MB
148. 174 04 Extract URLs And Text.mp438.75MB
149. 175 05 Work With Tags.mp438.63MB
150. 176 06 Work With Attributes.mp423.85MB
151. 177 07 Add Navigation To A String.mp424.29MB
152. 178 08 Navigate HTML Contents.mp461.44MB
153. 179 09 Find All Filter.mp432.42MB
154. 181 01 Project Preview.mp49.38MB
155. 182 02 What Is Plotly And Dash.mp418.69MB
156. 183 03 What You'll Need.mp410.75MB
157. 185 01 Build A Dash App.mp498.92MB
158. 186 02 Build A Graph In The Dash App.mp477.88MB
159. 188 01 Load Data From Vega Datasets.mp433.49MB
160. 189 02 Build The Layout.mp455.74MB
161. 190 03 Build A Chart With Altair.mp471.97MB
162. 192 01 Project Preview.mp415.63MB
163. 193 01 Build A Dataset.mp4141.13MB
164. 194 02 Compute Support And Confidence - If A Person Watches X, They Will Watch Y.mp464.77MB
165. 195 03 Compute Support And Confidence For All Channels.mp492.1MB
166. 196 04 Determine Which Videos Are Best To Recommend.mp467.8MB