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Complete Python & Data Analytics • Beginner to Advanced (2023-10)

chesskom
Oct 3rd, 2023 (edited)
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  1. Complete Python & Data Analytics • Beginner to Advanced
  2. 52 sections • 311 lectures • 42h 53m total length
  3. 2023-10 | e-Learning | English | MP4, ZIP | 36.03 GB
  4.  
  5. Learn Python Programming, Data Analysis & Wrangling with Pandas, Data Visualization and Machine Learning.
  6.  
  7.  
  8. DOWNLOAD:
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  10. https://rapidu.vip/5b9/com-py-n-dat-ana-beg-to-adv-2023-10.part01.rar
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  84. https://wrzucaj.pl/b0c66f7bff3e3d91/com-py-n-dat-ana-beg-to-adv-2023-10.part01.rar
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  95. https://wrzucaj.pl/a1f59f627adadc9f/com-py-n-dat-ana-beg-to-adv-2023-10.part12.rar
  96. https://wrzucaj.pl/7a41037579d1d01e/com-py-n-dat-ana-beg-to-adv-2023-10.part13.rar
  97. https://wrzucaj.pl/0d3e8f76ffe4e029/com-py-n-dat-ana-beg-to-adv-2023-10.part14.rar
  98. https://wrzucaj.pl/19ed9ce658e6f305/com-py-n-dat-ana-beg-to-adv-2023-10.part15.rar
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  100. https://wrzucaj.pl/8d3693502479b49e/com-py-n-dat-ana-beg-to-adv-2023-10.part17.rar
  101. https://wrzucaj.pl/fab9d0e5e66f9f29/com-py-n-dat-ana-beg-to-adv-2023-10.part18.rar
  102. https://wrzucaj.pl/82cd21e240ff26b1/com-py-n-dat-ana-beg-to-adv-2023-10.part19.rar
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  120. -------------------------
  121. https://rg.to/file/3d389be3041c9034eb896062655656db/com-py-n-dat-ana-beg-to-adv-2023-10.part01.rar
  122. https://rg.to/file/a44bf9a1569d2e1220d4ef9354a22a2b/com-py-n-dat-ana-beg-to-adv-2023-10.part02.rar
  123. https://rg.to/file/ec49a3880d9b76b315863af28ca30405/com-py-n-dat-ana-beg-to-adv-2023-10.part03.rar
  124. https://rg.to/file/dec775c49095b23904483a69468a8dbb/com-py-n-dat-ana-beg-to-adv-2023-10.part04.rar
  125. https://rg.to/file/35bc5e48a96b55b57be105687856405c/com-py-n-dat-ana-beg-to-adv-2023-10.part05.rar
  126. https://rg.to/file/5376fa243544ac112f8a532bf1acfbe3/com-py-n-dat-ana-beg-to-adv-2023-10.part06.rar
  127. https://rg.to/file/362787a3fec23cba784d4cd8d6869a83/com-py-n-dat-ana-beg-to-adv-2023-10.part07.rar
  128. https://rg.to/file/bc1c4c963fe1cdbeebfb9fb7c1235062/com-py-n-dat-ana-beg-to-adv-2023-10.part08.rar
  129. https://rg.to/file/7f94a544dd5cff44736d9ba8a159a67d/com-py-n-dat-ana-beg-to-adv-2023-10.part09.rar
  130. https://rg.to/file/5f8ea83cdd04481b1fb6c8831336283c/com-py-n-dat-ana-beg-to-adv-2023-10.part10.rar
  131. https://rg.to/file/01894db425b876cc71e5e18d57873dd4/com-py-n-dat-ana-beg-to-adv-2023-10.part11.rar
  132. https://rg.to/file/e950fb7e64a3010c1949cf86265c273b/com-py-n-dat-ana-beg-to-adv-2023-10.part12.rar
  133. https://rg.to/file/1a4c0931b0b13611630d8c9d5aaff38f/com-py-n-dat-ana-beg-to-adv-2023-10.part13.rar
  134. https://rg.to/file/90c7e00b9a0aea728ad554a618fb3c04/com-py-n-dat-ana-beg-to-adv-2023-10.part14.rar
  135. https://rg.to/file/b1b5acba6ebf3bbb8e77d60dc88432ed/com-py-n-dat-ana-beg-to-adv-2023-10.part15.rar
  136. https://rg.to/file/62e8211907d0937f9e5d7fad400892e2/com-py-n-dat-ana-beg-to-adv-2023-10.part16.rar
  137. https://rg.to/file/23854a2fe0439eb8445cf6d111acead2/com-py-n-dat-ana-beg-to-adv-2023-10.part17.rar
  138. https://rg.to/file/b40184722d365cd5e166b5219b0c2d9e/com-py-n-dat-ana-beg-to-adv-2023-10.part18.rar
  139. https://rg.to/file/a3829d21e1fcb8053cba01fd2e7c3614/com-py-n-dat-ana-beg-to-adv-2023-10.part19.rar
  140. https://rg.to/file/ed225b8de08222f8079ebd6b2616a430/com-py-n-dat-ana-beg-to-adv-2023-10.part20.rar
  141. https://rg.to/file/fb7473adab8e7189ac6c900d573d3e83/com-py-n-dat-ana-beg-to-adv-2023-10.part21.rar
  142. https://rg.to/file/182dc2c12afc8226c03494a8ba309fb7/com-py-n-dat-ana-beg-to-adv-2023-10.part22.rar
  143. https://rg.to/file/4f3b82a08c3f8140de2a81492aa92c7c/com-py-n-dat-ana-beg-to-adv-2023-10.part23.rar
  144. https://rg.to/file/aa3f9ad16b0503f4fc959e916be79c28/com-py-n-dat-ana-beg-to-adv-2023-10.part24.rar
  145. https://rg.to/file/7f37af3635845c9aece77ff43992794c/com-py-n-dat-ana-beg-to-adv-2023-10.part25.rar
  146. https://rg.to/file/f0da91774f2f95fb7d8c38d95fe723c3/com-py-n-dat-ana-beg-to-adv-2023-10.part26.rar
  147. https://rg.to/file/31d899bf44be418eb13a1d17a2b03b53/com-py-n-dat-ana-beg-to-adv-2023-10.part27.rar
  148. https://rg.to/file/3ce5adfdcc71283c9c0d0615c46a6686/com-py-n-dat-ana-beg-to-adv-2023-10.part28.rar
  149. https://rg.to/file/370a20e855b33fbdc012ea0711490aaa/com-py-n-dat-ana-beg-to-adv-2023-10.part29.rar
  150. https://rg.to/file/6d21fa7c33a0b787770d260d927d593d/com-py-n-dat-ana-beg-to-adv-2023-10.part30.rar
  151. https://rg.to/file/8826b68722a674fcc1c0e42d198b5a7b/com-py-n-dat-ana-beg-to-adv-2023-10.part31.rar
  152. https://rg.to/file/ef4b575c9ffa2b91f247b69fb3113e41/com-py-n-dat-ana-beg-to-adv-2023-10.part32.rar
  153. https://rg.to/file/dc19ddfbcad4268848fd03ab7a7f19a3/com-py-n-dat-ana-beg-to-adv-2023-10.part33.rar
  154. https://rg.to/file/ff00bc880703eba2ad008d190d43560e/com-py-n-dat-ana-beg-to-adv-2023-10.part34.rar
  155. https://rg.to/file/53294aa235c6a6dafade106edc348fff/com-py-n-dat-ana-beg-to-adv-2023-10.part35.rar
  156. https://rg.to/file/53bc3f8dc39664affbcc3017b459fe86/com-py-n-dat-ana-beg-to-adv-2023-10.part36.rar
  157. -------------------------
  158.  
  159.  
  160.  
  161. What you'll learn
  162. - Python coding - from Zero to Hero.
  163. - Realistic Data analysis and wrangling with Pandas.
  164. - Reshaping, merging, joining, and all sorts of complex data manipulations.
  165. - Handling Missing Values.
  166. - Groupby Operations (with Finance applications).
  167. - Time Series Resampling.
  168. - Complex Rolling Windows Operations.
  169. - OLS Linear Regressions.
  170. - Logistic Regressions.
  171. - Linear Discriminant Analysis.
  172. - Neural Networks.
  173. - Principal Component Analysis (PCA).
  174. - Support Vector Machines.
  175. - K-Nearest Neighbors Algorithm.
  176. - K-Means Clustering.
  177. - Professional data visualization with Seaborn.
  178. - Real-World Applications in Finance, Image/Facial Recognition, etc.
  179.  
  180. Requirements
  181. - No programming experience is required. You will learn everything you need to know about Python, data analytics and machine learning in this course.
  182. - Intermediate-level coders can directly proceed to Part 2 (Data Analytics with pandas).
  183.  
  184. Description
  185.  
  186. This course is a complete guide on Python & data analytics. You will learn everything they need to know to conduct data analysis and carry out data science using Python.
  187.  
  188. In particular, this course consists of 4 major parts ("mini-courses"):
  189.  
  190. 1. Python Crash Course for Beginners
  191. - All essential data types and common operations
  192. - Comprehensive string manipulations
  193. - Control flows
  194. - Lists, Tuples and Sets
  195. - Dictionaries
  196. - Object-Oriented Programming
  197. - Inheritance
  198. - Datetime
  199. - Modules and Packages
  200. - Exceptions Handling, etc.
  201.  
  202. 2. A Comprehensive Course on Data Analysis and Manipulation using Pandas
  203. - Series and Data Frames
  204. - Indexing, filtering, sorting, counting, etc.
  205. - Aggregation vs Transformation
  206. - Groupby
  207. - Reshape the data, pivot/melt
  208. - merge/join
  209. - missing values
  210. - apply, map
  211. - Time series computations & resampling
  212. - Rolling windows
  213. - Vectorized string and date/time manipulations, and many more
  214.  
  215. 3. A Complete Course on Data Visualization
  216. - pandas & seaborn
  217. - 15+ Types of Plots (relational, statistical, categorical)
  218. - Multi-plots with "facets", etc.
  219.  
  220. 4. An Applied Machine Learning Course using SciKit-Learn
  221. - Linear Regressions
  222. - Logistic Regressions
  223. - Linear Discriminant Analysis
  224. - Principal Component Analysis
  225. - K-Means
  226. - K-Nearest Neighbors
  227. - Support Vector Machines
  228. - Neural Networks
  229. - Hyper-parameters Tuning
  230. - Facial Recognition
  231. - Hand-written Digits Recognition, etc.
  232.  
  233. The course is one of the most comprehensive and detailed course ever on the Pandas package. It highlights the complexity of data wrangling which occupies about 80% of data scientists' time, and gives you a solid foundation to meet the challenging requirements of handling messy real-world data.
  234.  
  235. This course also introduces 8 most common ML algorithms and their applications in practical tasks such as image recognition and classifications. The focus is on applications and intuitive understanding rather than the underlying theories and mathematics.
  236.  
  237. By the end of this course, you will not only become a competent Python programmer, but also a skilled data analyst ready to take on real-world projects.
  238.  
  239. Who this course is for:
  240. - Absolute Beginners.
  241. - Intermediate-level Python coders who wants to level up their data analytics skills using Pandas and Machine Learning tools.
  242. - All aspiring data scientists, data analysts and data engineers.
  243. - Finance and business professionals/students (marketing, management, etc.).
  244. - Anyone who is curious about Python coding and/or data analytics.
  245.  
  246.  
  247.  
  248.  
  249. MORE COURSES:
  250. -----------------------------------------
  251. https://rg.to/folder/6531533/WEBSITE.html
  252. ---------------------------------------------
  253. https://rg.to/folder/6432280/PROGRAMMING.html
  254. ------------------------------------------------
  255. https://rg.to/folder/5704524/ENGLISH_COURSE.html
  256. ------------------------------------------------
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