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face=Calibri><U>TRAINING ON BIG DATA ANALYTICS USING
PYTHON<o:p></o:p></U></FONT></SPAN></STRONG></P>
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style='FONT-FAMILY: "Times New Roman",serif; COLOR: black; mso-color-alt: windowtext'>Introduction</SPAN></B><SPAN
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<P class=MsoNormal
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has been one of the most adaptable, and robust open-source languages that are
easy to learn and uses powerful libraries for data manipulation and analysis.
For many years now, Python has been used in scientific computing and
mathematical domains such as physics, finance, oil and gas, and signal
processing. This Big Data Analytics with Python course provides a complete
overview of data analysis techniques using Python. The Big Data Analytics with
Python course teaches you to master the concepts of Python programming. Through
this training, you will gain knowledge of the essential tools of Data Analytics
with Python.</SPAN><SPAN
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<P class=MsoNormal
style="BACKGROUND: white; TEXT-ALIGN: justify; MARGIN: 0in; LINE-HEIGHT: 16.9pt"><B><SPAN
style='FONT-SIZE: 11.5pt; FONT-FAMILY: "Times New Roman",serif; COLOR: black; mso-fareast-font-family: "Times New Roman"; mso-font-kerning: 0pt; mso-color-alt: windowtext'>Day
1: Introduction to Big Data and Python</SPAN></B><SPAN
style='FONT-SIZE: 11.5pt; FONT-FAMILY: "Times New Roman",serif; mso-fareast-font-family: "Times New Roman"; mso-font-kerning: 0pt'><o:p></o:p></SPAN></P>
<UL style="MARGIN-TOP: 0in" type=disc>
<LI class=MsoNormal
style="BACKGROUND: white; MARGIN: 0in; LINE-HEIGHT: 15.75pt; mso-list: l0 level1 lfo1; tab-stops: list .5in"><SPAN
style='FONT-SIZE: 10.5pt; FONT-FAMILY: "Times New Roman",serif; COLOR: black; mso-fareast-font-family: "Times New Roman"; mso-font-kerning: 0pt; mso-color-alt: windowtext'>Morning:</SPAN><SPAN
style='FONT-SIZE: 10.5pt; FONT-FAMILY: "Times New Roman",serif; mso-fareast-font-family: "Times New Roman"; mso-font-kerning: 0pt'><o:p></o:p></SPAN></LI>
<UL style="MARGIN-TOP: 0in" type=disc>
<LI class=MsoNormal
style="BACKGROUND: white; MARGIN: 0in; LINE-HEIGHT: 15.75pt; mso-list: l0 level2 lfo1; tab-stops: list 1.0in"><SPAN
style='FONT-SIZE: 10.5pt; FONT-FAMILY: "Times New Roman",serif; COLOR: black; mso-fareast-font-family: "Times New Roman"; mso-font-kerning: 0pt; mso-color-alt: windowtext'>Welcome
and Introduction to the Course</SPAN><SPAN
style='FONT-SIZE: 10.5pt; FONT-FAMILY: "Times New Roman",serif; mso-fareast-font-family: "Times New Roman"; mso-font-kerning: 0pt'><o:p></o:p></SPAN></LI>
<LI class=MsoNormal
style="BACKGROUND: white; MARGIN: 0in; LINE-HEIGHT: 15.75pt; mso-list: l0 level2 lfo1; tab-stops: list 1.0in"><SPAN
style='FONT-SIZE: 10.5pt; FONT-FAMILY: "Times New Roman",serif; COLOR: black; mso-fareast-font-family: "Times New Roman"; mso-font-kerning: 0pt; mso-color-alt: windowtext'>Overview
of Big Data and its Challenges</SPAN><SPAN
style='FONT-SIZE: 10.5pt; FONT-FAMILY: "Times New Roman",serif; mso-fareast-font-family: "Times New Roman"; mso-font-kerning: 0pt'><o:p></o:p></SPAN></LI>
<LI class=MsoNormal
style="BACKGROUND: white; MARGIN: 0in; LINE-HEIGHT: 15.75pt; mso-list: l0 level2 lfo1; tab-stops: list 1.0in"><SPAN
style='FONT-SIZE: 10.5pt; FONT-FAMILY: "Times New Roman",serif; COLOR: black; mso-fareast-font-family: "Times New Roman"; mso-font-kerning: 0pt; mso-color-alt: windowtext'>Introduction
to Python for Data Analytics</SPAN><SPAN
style='FONT-SIZE: 10.5pt; FONT-FAMILY: "Times New Roman",serif; mso-fareast-font-family: "Times New Roman"; mso-font-kerning: 0pt'><o:p></o:p></SPAN></LI>
<LI class=MsoNormal
style="BACKGROUND: white; MARGIN: 0in; LINE-HEIGHT: 15.75pt; mso-list: l0 level2 lfo1; tab-stops: list 1.0in"><SPAN
style='FONT-SIZE: 10.5pt; FONT-FAMILY: "Times New Roman",serif; COLOR: black; mso-fareast-font-family: "Times New Roman"; mso-font-kerning: 0pt; mso-color-alt: windowtext'>Setting
up Python Environment (Anaconda, Jupyter Notebook)</SPAN><SPAN
style='FONT-SIZE: 10.5pt; FONT-FAMILY: "Times New Roman",serif; mso-fareast-font-family: "Times New Roman"; mso-font-kerning: 0pt'><o:p></o:p></SPAN></LI></UL>
<LI class=MsoNormal
style="BACKGROUND: white; MARGIN: 0in; LINE-HEIGHT: 15.75pt; mso-list: l0 level1 lfo1; tab-stops: list .5in"><SPAN
style='FONT-SIZE: 10.5pt; FONT-FAMILY: "Times New Roman",serif; COLOR: black; mso-fareast-font-family: "Times New Roman"; mso-font-kerning: 0pt; mso-color-alt: windowtext'>Afternoon:</SPAN><SPAN
style='FONT-SIZE: 10.5pt; FONT-FAMILY: "Times New Roman",serif; mso-fareast-font-family: "Times New Roman"; mso-font-kerning: 0pt'><o:p></o:p></SPAN></LI>
<UL style="MARGIN-TOP: 0in" type=disc>
<LI class=MsoNormal
style="BACKGROUND: white; MARGIN: 0in; LINE-HEIGHT: 15.75pt; mso-list: l0 level2 lfo1; tab-stops: list 1.0in"><SPAN
style='FONT-SIZE: 10.5pt; FONT-FAMILY: "Times New Roman",serif; COLOR: black; mso-fareast-font-family: "Times New Roman"; mso-font-kerning: 0pt; mso-color-alt: windowtext'>Basic
Python Programming Concepts (Variables, Data Types, Loops,
Functions)</SPAN><SPAN
style='FONT-SIZE: 10.5pt; FONT-FAMILY: "Times New Roman",serif; mso-fareast-font-family: "Times New Roman"; mso-font-kerning: 0pt'><o:p></o:p></SPAN></LI>
<LI class=MsoNormal
style="BACKGROUND: white; MARGIN: 0in; LINE-HEIGHT: 15.75pt; mso-list: l0 level2 lfo1; tab-stops: list 1.0in"><SPAN
style='FONT-SIZE: 10.5pt; FONT-FAMILY: "Times New Roman",serif; COLOR: black; mso-fareast-font-family: "Times New Roman"; mso-font-kerning: 0pt; mso-color-alt: windowtext'>Introduction
to Pandas (DataFrames and Series)</SPAN><SPAN
style='FONT-SIZE: 10.5pt; FONT-FAMILY: "Times New Roman",serif; mso-fareast-font-family: "Times New Roman"; mso-font-kerning: 0pt'><o:p></o:p></SPAN></LI></UL></UL>
<P class=MsoNormal
style="BACKGROUND: white; TEXT-ALIGN: justify; MARGIN: 0in; LINE-HEIGHT: 16.9pt"><B><SPAN
style='FONT-SIZE: 11.5pt; FONT-FAMILY: "Times New Roman",serif; COLOR: black; mso-fareast-font-family: "Times New Roman"; mso-font-kerning: 0pt; mso-color-alt: windowtext'>Day
2: Data Manipulation and Preprocessing</SPAN></B><SPAN
style='FONT-SIZE: 11.5pt; FONT-FAMILY: "Times New Roman",serif; mso-fareast-font-family: "Times New Roman"; mso-font-kerning: 0pt'><o:p></o:p></SPAN></P>
<UL style="MARGIN-TOP: 0in" type=disc>
<LI class=MsoNormal
style="BACKGROUND: white; MARGIN: 0in; LINE-HEIGHT: 15.75pt; mso-list: l4 level1 lfo2; tab-stops: list .5in"><SPAN
style='FONT-SIZE: 10.5pt; FONT-FAMILY: "Times New Roman",serif; COLOR: black; mso-fareast-font-family: "Times New Roman"; mso-font-kerning: 0pt; mso-color-alt: windowtext'>Morning:</SPAN><SPAN
style='FONT-SIZE: 10.5pt; FONT-FAMILY: "Times New Roman",serif; mso-fareast-font-family: "Times New Roman"; mso-font-kerning: 0pt'><o:p></o:p></SPAN></LI>
<UL style="MARGIN-TOP: 0in" type=disc>
<LI class=MsoNormal
style="BACKGROUND: white; MARGIN: 0in; LINE-HEIGHT: 15.75pt; mso-list: l4 level2 lfo2; tab-stops: list 1.0in"><SPAN
style='FONT-SIZE: 10.5pt; FONT-FAMILY: "Times New Roman",serif; COLOR: black; mso-fareast-font-family: "Times New Roman"; mso-font-kerning: 0pt; mso-color-alt: windowtext'>Data
Cleaning and Handling Missing Values</SPAN><SPAN
style='FONT-SIZE: 10.5pt; FONT-FAMILY: "Times New Roman",serif; mso-fareast-font-family: "Times New Roman"; mso-font-kerning: 0pt'><o:p></o:p></SPAN></LI>
<LI class=MsoNormal
style="BACKGROUND: white; MARGIN: 0in; LINE-HEIGHT: 15.75pt; mso-list: l4 level2 lfo2; tab-stops: list 1.0in"><SPAN
style='FONT-SIZE: 10.5pt; FONT-FAMILY: "Times New Roman",serif; COLOR: black; mso-fareast-font-family: "Times New Roman"; mso-font-kerning: 0pt; mso-color-alt: windowtext'>Data
Transformation (e.g., filtering, sorting, merging)</SPAN><SPAN
style='FONT-SIZE: 10.5pt; FONT-FAMILY: "Times New Roman",serif; mso-fareast-font-family: "Times New Roman"; mso-font-kerning: 0pt'><o:p></o:p></SPAN></LI>
<LI class=MsoNormal
style="BACKGROUND: white; MARGIN: 0in; LINE-HEIGHT: 15.75pt; mso-list: l4 level2 lfo2; tab-stops: list 1.0in"><SPAN
style='FONT-SIZE: 10.5pt; FONT-FAMILY: "Times New Roman",serif; COLOR: black; mso-fareast-font-family: "Times New Roman"; mso-font-kerning: 0pt; mso-color-alt: windowtext'>Data
Visualization with Matplotlib and Seaborn</SPAN><SPAN
style='FONT-SIZE: 10.5pt; FONT-FAMILY: "Times New Roman",serif; mso-fareast-font-family: "Times New Roman"; mso-font-kerning: 0pt'><o:p></o:p></SPAN></LI></UL>
<LI class=MsoNormal
style="BACKGROUND: white; MARGIN: 0in; LINE-HEIGHT: 15.75pt; mso-list: l4 level1 lfo2; tab-stops: list .5in"><SPAN
style='FONT-SIZE: 10.5pt; FONT-FAMILY: "Times New Roman",serif; COLOR: black; mso-fareast-font-family: "Times New Roman"; mso-font-kerning: 0pt; mso-color-alt: windowtext'>Afternoon:</SPAN><SPAN
style='FONT-SIZE: 10.5pt; FONT-FAMILY: "Times New Roman",serif; mso-fareast-font-family: "Times New Roman"; mso-font-kerning: 0pt'><o:p></o:p></SPAN></LI>
<UL style="MARGIN-TOP: 0in" type=disc>
<LI class=MsoNormal
style="BACKGROUND: white; MARGIN: 0in; LINE-HEIGHT: 15.75pt; mso-list: l4 level2 lfo2; tab-stops: list 1.0in"><SPAN
style='FONT-SIZE: 10.5pt; FONT-FAMILY: "Times New Roman",serif; COLOR: black; mso-fareast-font-family: "Times New Roman"; mso-font-kerning: 0pt; mso-color-alt: windowtext'>Introduction
to NumPy for Numerical Operations</SPAN><SPAN
style='FONT-SIZE: 10.5pt; FONT-FAMILY: "Times New Roman",serif; mso-fareast-font-family: "Times New Roman"; mso-font-kerning: 0pt'><o:p></o:p></SPAN></LI>
<LI class=MsoNormal
style="BACKGROUND: white; MARGIN: 0in; LINE-HEIGHT: 15.75pt; mso-list: l4 level2 lfo2; tab-stops: list 1.0in"><SPAN
style='FONT-SIZE: 10.5pt; FONT-FAMILY: "Times New Roman",serif; COLOR: black; mso-fareast-font-family: "Times New Roman"; mso-font-kerning: 0pt; mso-color-alt: windowtext'>Exploratory
Data Analysis (EDA)</SPAN><SPAN
style='FONT-SIZE: 10.5pt; FONT-FAMILY: "Times New Roman",serif; mso-fareast-font-family: "Times New Roman"; mso-font-kerning: 0pt'><o:p></o:p></SPAN></LI>
<LI class=MsoNormal
style="BACKGROUND: white; MARGIN: 0in; LINE-HEIGHT: 15.75pt; mso-list: l4 level2 lfo2; tab-stops: list 1.0in"><SPAN
style='FONT-SIZE: 10.5pt; FONT-FAMILY: "Times New Roman",serif; COLOR: black; mso-fareast-font-family: "Times New Roman"; mso-font-kerning: 0pt; mso-color-alt: windowtext'>Case
Study: Exploring a Real-world Dataset</SPAN><SPAN
style='FONT-SIZE: 10.5pt; FONT-FAMILY: "Times New Roman",serif; mso-fareast-font-family: "Times New Roman"; mso-font-kerning: 0pt'><o:p></o:p></SPAN></LI></UL></UL>
<P class=MsoNormal
style="BACKGROUND: white; TEXT-ALIGN: justify; MARGIN: 0in; LINE-HEIGHT: 16.9pt"><B><SPAN
style='FONT-SIZE: 11.5pt; FONT-FAMILY: "Times New Roman",serif; COLOR: black; mso-fareast-font-family: "Times New Roman"; mso-font-kerning: 0pt; mso-color-alt: windowtext'>Day
3: Big Data Tools and Distributed Computing</SPAN></B><SPAN
style='FONT-SIZE: 11.5pt; FONT-FAMILY: "Times New Roman",serif; mso-fareast-font-family: "Times New Roman"; mso-font-kerning: 0pt'><o:p></o:p></SPAN></P>
<UL style="MARGIN-TOP: 0in" type=disc>
<LI class=MsoNormal
style="BACKGROUND: white; MARGIN: 0in; LINE-HEIGHT: 15.75pt; mso-list: l1 level1 lfo3; tab-stops: list .5in"><SPAN
style='FONT-SIZE: 10.5pt; FONT-FAMILY: "Times New Roman",serif; COLOR: black; mso-fareast-font-family: "Times New Roman"; mso-font-kerning: 0pt; mso-color-alt: windowtext'>Morning:</SPAN><SPAN
style='FONT-SIZE: 10.5pt; FONT-FAMILY: "Times New Roman",serif; mso-fareast-font-family: "Times New Roman"; mso-font-kerning: 0pt'><o:p></o:p></SPAN></LI>
<UL style="MARGIN-TOP: 0in" type=disc>
<LI class=MsoNormal
style="BACKGROUND: white; MARGIN: 0in; LINE-HEIGHT: 15.75pt; mso-list: l1 level2 lfo3; tab-stops: list 1.0in"><SPAN
style='FONT-SIZE: 10.5pt; FONT-FAMILY: "Times New Roman",serif; COLOR: black; mso-fareast-font-family: "Times New Roman"; mso-font-kerning: 0pt; mso-color-alt: windowtext'>Introduction
to Big Data Technologies (Hadoop, Spark)</SPAN><SPAN
style='FONT-SIZE: 10.5pt; FONT-FAMILY: "Times New Roman",serif; mso-fareast-font-family: "Times New Roman"; mso-font-kerning: 0pt'><o:p></o:p></SPAN></LI>
<LI class=MsoNormal
style="BACKGROUND: white; MARGIN: 0in; LINE-HEIGHT: 15.75pt; mso-list: l1 level2 lfo3; tab-stops: list 1.0in"><SPAN
style='FONT-SIZE: 10.5pt; FONT-FAMILY: "Times New Roman",serif; COLOR: black; mso-fareast-font-family: "Times New Roman"; mso-font-kerning: 0pt; mso-color-alt: windowtext'>Overview
of HDFS (Hadoop Distributed File System)</SPAN><SPAN
style='FONT-SIZE: 10.5pt; FONT-FAMILY: "Times New Roman",serif; mso-fareast-font-family: "Times New Roman"; mso-font-kerning: 0pt'><o:p></o:p></SPAN></LI>
<LI class=MsoNormal
style="BACKGROUND: white; MARGIN: 0in; LINE-HEIGHT: 15.75pt; mso-list: l1 level2 lfo3; tab-stops: list 1.0in"><SPAN
style='FONT-SIZE: 10.5pt; FONT-FAMILY: "Times New Roman",serif; COLOR: black; mso-fareast-font-family: "Times New Roman"; mso-font-kerning: 0pt; mso-color-alt: windowtext'>Setting
up a Hadoop/Spark Cluster (Local or Cloud)</SPAN><SPAN
style='FONT-SIZE: 10.5pt; FONT-FAMILY: "Times New Roman",serif; mso-fareast-font-family: "Times New Roman"; mso-font-kerning: 0pt'><o:p></o:p></SPAN></LI></UL>
<LI class=MsoNormal
style="BACKGROUND: white; MARGIN: 0in; LINE-HEIGHT: 15.75pt; mso-list: l1 level1 lfo3; tab-stops: list .5in"><SPAN
style='FONT-SIZE: 10.5pt; FONT-FAMILY: "Times New Roman",serif; COLOR: black; mso-fareast-font-family: "Times New Roman"; mso-font-kerning: 0pt; mso-color-alt: windowtext'>Afternoon:</SPAN><SPAN
style='FONT-SIZE: 10.5pt; FONT-FAMILY: "Times New Roman",serif; mso-fareast-font-family: "Times New Roman"; mso-font-kerning: 0pt'><o:p></o:p></SPAN></LI>
<UL style="MARGIN-TOP: 0in" type=disc>
<LI class=MsoNormal
style="BACKGROUND: white; MARGIN: 0in; LINE-HEIGHT: 15.75pt; mso-list: l1 level2 lfo3; tab-stops: list 1.0in"><SPAN
style='FONT-SIZE: 10.5pt; FONT-FAMILY: "Times New Roman",serif; COLOR: black; mso-fareast-font-family: "Times New Roman"; mso-font-kerning: 0pt; mso-color-alt: windowtext'>Introduction
to PySpark</SPAN><SPAN
style='FONT-SIZE: 10.5pt; FONT-FAMILY: "Times New Roman",serif; mso-fareast-font-family: "Times New Roman"; mso-font-kerning: 0pt'><o:p></o:p></SPAN></LI>
<LI class=MsoNormal
style="BACKGROUND: white; MARGIN: 0in; LINE-HEIGHT: 15.75pt; mso-list: l1 level2 lfo3; tab-stops: list 1.0in"><SPAN
style='FONT-SIZE: 10.5pt; FONT-FAMILY: "Times New Roman",serif; COLOR: black; mso-fareast-font-family: "Times New Roman"; mso-font-kerning: 0pt; mso-color-alt: windowtext'>Working
with RDDs (Resilient Distributed Datasets)</SPAN><SPAN
style='FONT-SIZE: 10.5pt; FONT-FAMILY: "Times New Roman",serif; mso-fareast-font-family: "Times New Roman"; mso-font-kerning: 0pt'><o:p></o:p></SPAN></LI>
<LI class=MsoNormal
style="BACKGROUND: white; MARGIN: 0in; LINE-HEIGHT: 15.75pt; mso-list: l1 level2 lfo3; tab-stops: list 1.0in"><SPAN
style='FONT-SIZE: 10.5pt; FONT-FAMILY: "Times New Roman",serif; COLOR: black; mso-fareast-font-family: "Times New Roman"; mso-font-kerning: 0pt; mso-color-alt: windowtext'>Basic
Data Processing with PySpark</SPAN><SPAN
style='FONT-SIZE: 10.5pt; FONT-FAMILY: "Times New Roman",serif; mso-fareast-font-family: "Times New Roman"; mso-font-kerning: 0pt'><o:p></o:p></SPAN></LI></UL></UL>
<P class=MsoNormal
style="BACKGROUND: white; TEXT-ALIGN: justify; MARGIN: 0in; LINE-HEIGHT: 16.9pt"><B><SPAN
style='FONT-SIZE: 11.5pt; FONT-FAMILY: "Times New Roman",serif; COLOR: black; mso-fareast-font-family: "Times New Roman"; mso-font-kerning: 0pt; mso-color-alt: windowtext'>Day
4: Advanced Data Analytics with Python</SPAN></B><SPAN
style='FONT-SIZE: 11.5pt; FONT-FAMILY: "Times New Roman",serif; mso-fareast-font-family: "Times New Roman"; mso-font-kerning: 0pt'><o:p></o:p></SPAN></P>
<UL style="MARGIN-TOP: 0in" type=disc>
<LI class=MsoNormal
style="BACKGROUND: white; MARGIN: 0in; LINE-HEIGHT: 15.75pt; mso-list: l3 level1 lfo4; tab-stops: list .5in"><SPAN
style='FONT-SIZE: 10.5pt; FONT-FAMILY: "Times New Roman",serif; COLOR: black; mso-fareast-font-family: "Times New Roman"; mso-font-kerning: 0pt; mso-color-alt: windowtext'>Morning:</SPAN><SPAN
style='FONT-SIZE: 10.5pt; FONT-FAMILY: "Times New Roman",serif; mso-fareast-font-family: "Times New Roman"; mso-font-kerning: 0pt'><o:p></o:p></SPAN></LI>
<UL style="MARGIN-TOP: 0in" type=disc>
<LI class=MsoNormal
style="BACKGROUND: white; MARGIN: 0in; LINE-HEIGHT: 15.75pt; mso-list: l3 level2 lfo4; tab-stops: list 1.0in"><SPAN
style='FONT-SIZE: 10.5pt; FONT-FAMILY: "Times New Roman",serif; COLOR: black; mso-fareast-font-family: "Times New Roman"; mso-font-kerning: 0pt; mso-color-alt: windowtext'>Machine
Learning with Scikit-Learn</SPAN><SPAN
style='FONT-SIZE: 10.5pt; FONT-FAMILY: "Times New Roman",serif; mso-fareast-font-family: "Times New Roman"; mso-font-kerning: 0pt'><o:p></o:p></SPAN></LI>
<LI class=MsoNormal
style="BACKGROUND: white; MARGIN: 0in; LINE-HEIGHT: 15.75pt; mso-list: l3 level2 lfo4; tab-stops: list 1.0in"><SPAN
style='FONT-SIZE: 10.5pt; FONT-FAMILY: "Times New Roman",serif; COLOR: black; mso-fareast-font-family: "Times New Roman"; mso-font-kerning: 0pt; mso-color-alt: windowtext'>Model
Training and Evaluation</SPAN><SPAN
style='FONT-SIZE: 10.5pt; FONT-FAMILY: "Times New Roman",serif; mso-fareast-font-family: "Times New Roman"; mso-font-kerning: 0pt'><o:p></o:p></SPAN></LI>
<LI class=MsoNormal
style="BACKGROUND: white; MARGIN: 0in; LINE-HEIGHT: 15.75pt; mso-list: l3 level2 lfo4; tab-stops: list 1.0in"><SPAN
style='FONT-SIZE: 10.5pt; FONT-FAMILY: "Times New Roman",serif; COLOR: black; mso-fareast-font-family: "Times New Roman"; mso-font-kerning: 0pt; mso-color-alt: windowtext'>Feature
Engineering</SPAN><SPAN
style='FONT-SIZE: 10.5pt; FONT-FAMILY: "Times New Roman",serif; mso-fareast-font-family: "Times New Roman"; mso-font-kerning: 0pt'><o:p></o:p></SPAN></LI></UL>
<LI class=MsoNormal
style="BACKGROUND: white; MARGIN: 0in; LINE-HEIGHT: 15.75pt; mso-list: l3 level1 lfo4; tab-stops: list .5in"><SPAN
style='FONT-SIZE: 10.5pt; FONT-FAMILY: "Times New Roman",serif; COLOR: black; mso-fareast-font-family: "Times New Roman"; mso-font-kerning: 0pt; mso-color-alt: windowtext'>Afternoon:</SPAN><SPAN
style='FONT-SIZE: 10.5pt; FONT-FAMILY: "Times New Roman",serif; mso-fareast-font-family: "Times New Roman"; mso-font-kerning: 0pt'><o:p></o:p></SPAN></LI>
<UL style="MARGIN-TOP: 0in" type=disc>
<LI class=MsoNormal
style="BACKGROUND: white; MARGIN: 0in; LINE-HEIGHT: 15.75pt; mso-list: l3 level2 lfo4; tab-stops: list 1.0in"><SPAN
style='FONT-SIZE: 10.5pt; FONT-FAMILY: "Times New Roman",serif; COLOR: black; mso-fareast-font-family: "Times New Roman"; mso-font-kerning: 0pt; mso-color-alt: windowtext'>Introduction
to Deep Learning with TensorFlow/Keras</SPAN><SPAN
style='FONT-SIZE: 10.5pt; FONT-FAMILY: "Times New Roman",serif; mso-fareast-font-family: "Times New Roman"; mso-font-kerning: 0pt'><o:p></o:p></SPAN></LI>
<LI class=MsoNormal
style="BACKGROUND: white; MARGIN: 0in; LINE-HEIGHT: 15.75pt; mso-list: l3 level2 lfo4; tab-stops: list 1.0in"><SPAN
style='FONT-SIZE: 10.5pt; FONT-FAMILY: "Times New Roman",serif; COLOR: black; mso-fareast-font-family: "Times New Roman"; mso-font-kerning: 0pt; mso-color-alt: windowtext'>Neural
Networks and Deep Learning Concepts</SPAN><SPAN
style='FONT-SIZE: 10.5pt; FONT-FAMILY: "Times New Roman",serif; mso-fareast-font-family: "Times New Roman"; mso-font-kerning: 0pt'><o:p></o:p></SPAN></LI>
<LI class=MsoNormal
style="BACKGROUND: white; MARGIN: 0in; LINE-HEIGHT: 15.75pt; mso-list: l3 level2 lfo4; tab-stops: list 1.0in"><SPAN
style='FONT-SIZE: 10.5pt; FONT-FAMILY: "Times New Roman",serif; COLOR: black; mso-fareast-font-family: "Times New Roman"; mso-font-kerning: 0pt; mso-color-alt: windowtext'>Hands-on
Deep Learning Exercise</SPAN><SPAN
style='FONT-SIZE: 10.5pt; FONT-FAMILY: "Times New Roman",serif; mso-fareast-font-family: "Times New Roman"; mso-font-kerning: 0pt'><o:p></o:p></SPAN></LI></UL></UL>
<P class=MsoNormal
style="BACKGROUND: white; TEXT-ALIGN: justify; MARGIN: 0in; LINE-HEIGHT: 16.9pt"><B><SPAN
style='FONT-SIZE: 11.5pt; FONT-FAMILY: "Times New Roman",serif; COLOR: black; mso-fareast-font-family: "Times New Roman"; mso-font-kerning: 0pt; mso-color-alt: windowtext'>Day
5: Big Data Analytics and Conclusion</SPAN></B><SPAN
style='FONT-SIZE: 11.5pt; FONT-FAMILY: "Times New Roman",serif; mso-fareast-font-family: "Times New Roman"; mso-font-kerning: 0pt'><o:p></o:p></SPAN></P>
<UL style="MARGIN-TOP: 0in" type=disc>
<LI class=MsoNormal
style="BACKGROUND: white; MARGIN: 0in; LINE-HEIGHT: 15.75pt; mso-list: l2 level1 lfo5; tab-stops: list .5in"><SPAN
style='FONT-SIZE: 10.5pt; FONT-FAMILY: "Times New Roman",serif; COLOR: black; mso-fareast-font-family: "Times New Roman"; mso-font-kerning: 0pt; mso-color-alt: windowtext'>Morning:</SPAN><SPAN
style='FONT-SIZE: 10.5pt; FONT-FAMILY: "Times New Roman",serif; mso-fareast-font-family: "Times New Roman"; mso-font-kerning: 0pt'><o:p></o:p></SPAN></LI>
<UL style="MARGIN-TOP: 0in" type=disc>
<LI class=MsoNormal
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style='FONT-SIZE: 10.5pt; FONT-FAMILY: "Times New Roman",serif; COLOR: black; mso-fareast-font-family: "Times New Roman"; mso-font-kerning: 0pt; mso-color-alt: windowtext'>Large-scale
Data Processing with PySpark</SPAN><SPAN
style='FONT-SIZE: 10.5pt; FONT-FAMILY: "Times New Roman",serif; mso-fareast-font-family: "Times New Roman"; mso-font-kerning: 0pt'><o:p></o:p></SPAN></LI>
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style='FONT-SIZE: 10.5pt; FONT-FAMILY: "Times New Roman",serif; COLOR: black; mso-fareast-font-family: "Times New Roman"; mso-font-kerning: 0pt; mso-color-alt: windowtext'>Building
Data Pipelines</SPAN><SPAN
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Data Processing (Optional)</SPAN><SPAN
style='FONT-SIZE: 10.5pt; FONT-FAMILY: "Times New Roman",serif; mso-fareast-font-family: "Times New Roman"; mso-font-kerning: 0pt'><o:p></o:p></SPAN></LI></UL>
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style='FONT-SIZE: 10.5pt; FONT-FAMILY: "Times New Roman",serif; COLOR: black; mso-fareast-font-family: "Times New Roman"; mso-font-kerning: 0pt; mso-color-alt: windowtext'>Afternoon:</SPAN><SPAN
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<UL style="MARGIN-TOP: 0in" type=disc>
<LI class=MsoNormal
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style='FONT-SIZE: 10.5pt; FONT-FAMILY: "Times New Roman",serif; COLOR: black; mso-fareast-font-family: "Times New Roman"; mso-font-kerning: 0pt; mso-color-alt: windowtext'>Final
Project: Applying Big Data Analytics on a Real Dataset</SPAN><SPAN
style='FONT-SIZE: 10.5pt; FONT-FAMILY: "Times New Roman",serif; mso-fareast-font-family: "Times New Roman"; mso-font-kerning: 0pt'><o:p></o:p></SPAN></LI>
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of Projects</SPAN><SPAN
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Session</SPAN><SPAN
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style='FONT-SIZE: 10.5pt; FONT-FAMILY: "Times New Roman",serif; COLOR: black; mso-fareast-font-family: "Times New Roman"; mso-font-kerning: 0pt; mso-color-alt: windowtext'>Course
Conclusion and Certification</SPAN><SPAN
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