Open Class: Python for Data Science - The Why, What & How

With our big data experts, WeCloudData prepares you for the next generation of data science challenges and offers everything you need to succeed in career transformation. WeCloudData is the leading data science education and career service provider in Canada. We are the bridge between devoted and passionate data scientists and companies who need help with challenging business problems in data analytics.

WeCloudData

<IMG SRC="https://cdn.evbuc.com/eventlogos/174288436/screenshot20160704at9.29.57am.jpg"> 
Python is hot!!! Youtube, Dropbox, Quora, Eventbrite and many other famous Internet companies are built on python. Data Scientists and Analysts love to use python for data analysis and machine learning, data engineers like to use python for scripting and DevOps, big data expersts use python to handle data at scale and build data pipelines, and developers use python to build web applciations.
Python has been hailed as one of the staples for programming in data science field. It is among the top ten in-demand technologies around world, and it is listed as one of the top ten highest-paying tech skills with salary over $100,000.  It is powerful enough for experienced programmers to build real-world products, but also simple enough for beginners to pick up and jump start on meaningful projects in a short period of time.
WeCloudData invited two experienced data scientists from Kik and the Globe and Mail, which have formed data science team a few years ago, to share the python use cases from the projects they dealt with in their everyday's work.
We will offer a free info session of our key python course to those who are interested in honing their python skills for data science through a series of projects and preparing for the data science jobs in Canada. With our carefully designed projects, experienced teaching team, and on-going support, we are confident that you will be comfortable taking on challenges that big data analytics throws at you after finishing the course. 
 
<H2 CLASS="MsoNormal">Please bring your laptop, so that you can enjoy the fun of hands-on lab!</H2>
<H2 CLASS="MsoNormal">Speakers:</H2>
<H3>Rex Liu</H3>
Rex Liu has years of working experience as data engineer/ data scientist at BlackBerry and The Globe and Mail. He is experienced with big data analytics through working with substantial amount of unstructured, heterogeneous data in research-driven and business-driven projects. He builds machine learning and statistical analysis models that become crucial parts of business decision making.
Rex has earned a Master of Science degree in Computer Science, focusing on machine learning and natural language processing (NLP) from University of Ottawa. During his study he had published research papers in international academic conferences, covering fields such as language modelling, deep learning and social media data mining.
 
<H3>Shaohua Zhang</H3>
A self-trained data scientist and an expert in applied big data technologies, Shaohua has 9 years of experience in applied data science and has built a reputation for building high-performance data science teams. He is currently a senior data scientist at Kik Interactive Inc., helping the billion-dollar Canadian tech unicorn grow its big data initiative. 
Prior to Kik, Shaohua built a high-performance data science team at BlackBerry that focused on building innovative data science solutions for marketing, CRM and product teams. His is specialized in user interest graph modelling, targeted advertising, scalable location intelligence and large-scale recommendation engines for mobile personalization. He also collaborated with Ryerson’s Data Science Lab on several big data research projects. Shaohua also helped build the big data course at Ryerson University where he trained over 150 professionals on big data technologies such as Hadoop, Spark and data sciences.
 
<H2 CLASS="MsoNormal">Why Choosing WeCloudData?</H2>
<UL>
<LI>Our instructors  
<UL>
<LI>Our instructors play key roles in data science organizations in some of the most well-known data-driven companies in North America</LI>
<LI>Our instructors use python, spark and cloud platforms on a daily basis to tackle data science/engineering problems</LI>
<LI>Our instructors are good presenters and story tellers</LI>
<LI>WeCloudData has gathered the top talents to design the most comprehensive, effective and cost-efficient learning path to help you land your first data scientist job.</LI>
</UL>
</LI>
</UL>
<UL>
<LI>Course and Learning Path
<UL>
<LI>Course is designed with practicality in mind</LI>
<LI>Our course is designed to solidify your coding skills through a huge range of real-world projects derived from industry trend as well as from our experts’ work experience.</LI>
<LI>Our instructors use python every day and they teach students to focus on things that actually matter in workplace</LI>
<LI>Python programming for data science is the foundation for big data, data science and data engineering tracks</LI>
</UL>
</LI>
</UL>
<UL>
<LI>Capstone projects (7)
<UL>
<LI>Apart from the lab exercises we provide for each class, we also ask students to involve in 7 mini-projects after class. And our TA's will provide timely online support via email or any social media you’re comfortable with.</LI>
<LI>7 mini-projects will cover data collection via web APIs, data preparation with pandas, web scraping, structured table manipulation and excel automation, database and queries, data visualizations</LI>
</UL>
</LI>
</UL>
<UL>
<LI>Office hours/Online support
<UL>
<LI>During the 2 months learning period, we believe effective learning happens outside the classroom through practice and reinforcement. Our TA's and instructors provide office hours and also online support. It is our belief that being able to address students’ questions face to face will yield the best learning outcome. </LI>
<LI>You will get a one-on-one coffee meeting with instructors who will learn about your career goal, needs, strengths and short boards. We will offer practical advices to help you get your dream offer.</LI>
</UL>
</LI>
</UL>
 
<H2 CLASS="MsoNormal">Course Syllabus</H2>
 
Week 1: Introduction to Python for Data Science
 
A Brief Introduction to Python
Python for Data Science - The Landscape
Environment Setup
         Anaconda
         IPython Jupyter Notebook
         PySpark
Lab Exercises
         Linux Commands for Data Science
         IPython Notebook Introduction 
 
 
Week 2: Text Analysis 
           Python Data Types
 
Use Case 
         Data Science - Text Analysis 
Project 1
         Regular Expression and Basic Text Processing
Topics
         Basic data types
                   numbers
                   strings
                   booleans
         Advanced data types
                   lists
                   tuples
                   dictionaries
Lab Exercises
         Regular Expression lab
 
 
Week 3: Social Media Analysis
           Basic Python Programming
 
Use Case
         Data Science - Social Media Analysis
Project 2
         Working with Web APIs - Twitter, Facebook, LinkedIn
Topics
         Operators in Python
         Conditional statements
         Loops
         Lambdas and functions
         Regular expression in Python
         File IO in Python: working with various file types such as text, Excel and JSON
         Serialization with pickle
Lab Exercises
         Python basics exercises
 
Week 4: Unsupervised learning
           Numpy I
 
Use Case
Data Science - Clustering and Segmentation
Project 3
         K-Means Clustering with Numpy
Topics
         Review of basic statistics
         Numpy
                   ndarrays
                            creating arrays
                            array manipulations 
                   indexing and slicing
                   shape operations
                   advanced indexing
Lab Exercises
         Numpy Exercises
 
 
Week 5: Supervised learning
           Numpy II & Scipy
 
Use Case
Data Science - Predictive Analytics
Project 4
         Logistic Regression with Numpy & Scipy
Topics
         Numpy
                   copy data with arrays
                   advanced techniques
         Scipy
                   advanced numeric algorithms in scipy
                   linear algebra with scipy
                   statistics with scipy
Lab Exercises
         Scipy Exercises
         Machine Learning with PySpark MLlib - KMeans
 
 
 
 
Week 6: Working with SQL & Databases
           Pandas I
 
Use Case
Data Science - SQL & Databases
Project 5
         Working with Databases Using Python and SQL
Topics 
         pandas series
         pandas dataframes
         basic operations
                   indexing
                   slicing rows and columns
                   sorting data
         summary statistics
         handling missing data, outliers and duplicates
Lab Exercises
         Pandas exercises
 
Week 7: Big Data and Spark
           Pandas II and Pyspark
 
Use Case
Data Science - Big Data and Spark
Project 6
         Working with Big Data Using Python, SparkSQL and DataFrames
Topics 
         Advanced operations:
                   advanced indexing and slicing
                   GroupBy
                   aggregating data
                   shape operations
                   merging series and dataframes
                   pivoting
         File IO with pandas
                   working with .txt files
                   working with Excel files
                   working with .csv files
         Working directly with web data
                   downloadable data
                   data on webpages
Lab Exercises
         Web Scraping with Python & BeautifulSoup
 
 
Week 8: Digital Marketing & A/B Testing
           Data Visualization
 
Use Case
Data Science - Digital Marketing & A/B Testing
Project 7
         
         Data Visualizations with Matplotlib, Seaborn and Plot.ly
Topics
         plotting with pandas
         plotting with matplotlib: basic
                   simply plots
                   customizing plots with matplotlib
         plotting with matplotlib: advanced
                   histograms
                   bar charts
                   pie charts
                   3D plots
                   scatter plots
                   financial charts
                   plotting on maps with Basemap
         plotting with Seaborn
         plotting with <A HREF="http://plot.ly" TARGET="_blank" DATA-MSYS-CLICKTRACK="0" REL="nofollow noopener noreferrer">plot.ly</A>
Lab Exercises
         Using <A HREF="http://plot.ly" TARGET="_blank" DATA-MSYS-CLICKTRACK="0" REL="nofollow noopener noreferrer">plot.ly</A> for measuring marketing campaigns       
 
 
Review
         Course review
         Where to go next
         Improve your résumé
            Project review

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Open Class: Python for Data Science - The Why, What & How

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