首页
<source id="3oodw" ><sup id="3oodw" ></sup></source>

      1. <s id="3oodw" ><th id="3oodw" ><small id="3oodw" ></small></th></s>
        <i id="3oodw" ><optgroup id="3oodw" ></optgroup></i>

            <input id="3oodw" ><bdo id="3oodw" ><cite id="3oodw" ></cite></bdo></input>
            <delect id="3oodw" ><ruby id="3oodw" ></ruby></delect>

            <em id="3oodw" ><progress id="3oodw" ></progress></em><input id="3oodw" ></input>
            <strike id="3oodw" ></strike>
             

            Events  Classes  Deals  Spaces  Jobs 
                Sign in  
             
             
            With Tony Schultz (Data Science Instructor, NYC Data Science Academy) & Alexander Baransky (Data Science Trainer & Program Mgr, NYC Data Science Academy).
            Monday, April 20, 中国体彩官网app下载 at 07:00 PM   Not Known
            Online
             
             
               
             
             
                          

                    
             
            Sign up for our awesome New York
            Tech Events weekly email newsletter.
               
            EVENT DETAILS
            Course Overview
            This is a class for computer-literate people with no programming background who wish to learn basic Python programming. The course is aimed at those who want to learn data wrangling - manipulating downloaded files to make them amenable to analysis. We concentrate on language basics such as list & string manipulation, control structures, simple data analysis packages, & introduce modules for downloading data from the web.

            * Tuition paid for part-time courses can be applied to the Data Science Bootcamp if admitted within 9 months.

            Instructors
            Tony Schultz
            Tony Schultz
            Tony received his Ph.D. in Physics from the City University of New York & has taught at Sarah Lawrence College中国体彩官网app下载 over the past decade. Tony specializes in developing machine learning & pattern recognition algorithms for processing motion capture data. He is passionate about teaching scientific computing & studying deep structures in human motion.
            Alexander Baransky
            Alexander Baransky
            Alex received his degree in Environmental Biology from Columbia University. He has experience with multiple computer languages including Python, R, & SQL. As an engineer at heart & biologist through training, Alex is passionate about animal behavior & finding innovative ways to use data science in the field of biology.

            This Introductory Python class is designed for computer-literate people with no programming background who wish to learn basic Python programming. The course is aimed at those who want to learn data wrangling - manipulating downloaded files to make them amenable to analysis. We concentrate on language basics such as list & string manipulation, control structures, simple data analysis packages, & introduce modules for downloading data from the web.

            This Introductory Python class runs over four weeks, with five hours of class per week (split into 2 hour evening classes). Classes will be given in a lab setting, with student exercises mixed with lectures. Students should bring a laptop to class. There will be a modest amount of 中国体彩官网app下载work after each class. Due to the focused nature of this course, there will be no individual class projects but the instructors will be available to help students who are applying Python to their own work outside of class.

            Certificate
            Certificates are awarded at the end of the program at the satisfactory completion of the course.

            Students are evaluated on a pass/fail basis for their performance on the required 中国体彩官网app下载work & final project (where applicable). Students who complete 80% of the 中国体彩官网app下载work & attend a minimum of 85% of all classes are eligible for the certificate of completion.

            Syllabus
            Unit 1: List manipulation

            Simple values & expressions
            Defining functions, using ordinary syntax & lambda syntax
            Lists
            Built-in functions & subscripting
            Nested lists
            Functional operators: map & filter
            List Comprehensions
            Multiple-list operations: map & zip
            Functional operators: reduce
            Unit 2: Strings & simple I/O

            Characters
            Strings as lists of characters
            Built-in string operations
            Input files as lists of strings
            Print statement
            Reading data from the web
            Using the requests package
            String-based web scraping (e.g. handling csv files)
            Unit 3: Control structures

            Statements vs. expressions
            For loops
            Variables in for loops
            if statements
            Simple & nested if statements
            Conditional expressions in lambda functions
            While loops
            break & continue
            Unit 4: Data Analysis Packages

            NumPy
            Ndarray
            Subscripting & slicing
            Operations
            Pandas
            Data Structure
            Data Manipulation
            Grouping & Aggregation
            Preparation - How to set up Python environment

            [IMPORTANT] In the class we will use Python 3. If you are following this video to set up Python environment, please make sure you download the Python 3.X version starting from 1 min 23 s in the video.
             
             
             
             
            © 中国体彩官网app下载 GarysGuide      About    Feedback    Press    Terms