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Introduction to Data Science with Python

6 week Hands-On Certificate Course on:

Introduction:

The Data Science with Python Certificate program offers you the opportunity to learn the most important programming languages used by data scientists today. Get your start in the fascinating field of data science and learn Python, SQL and git with the help of experienced instructors. You will emerge prepared to tackle real-world data analysis problems.

WHO SHOULD ATTEND THIS COURSE

Students, Academicians or Industry professionals from any educational background can attend this certificate course. This course will enable the person to adapt and develop his or her capacity to interact with the current technological changes. All you need is a basic understanding of how a computer works.

PROGRAM OVERVIEW

Course 1: Introduction to SQL

The first course will teach you the fundamentals of SQL such as JOINs and Aggregations. Learn how to use SQL to answer complex business problems.

Lesson Title Learning Outcomes
BASIC SQL
  • Write common SQL commands including SELECT, FROM, and WHERE.
  • Learn how to use logical operators like LIKE, AND, and OR.
SQL JOINS
  • Write JOINs in SQL, as you are now able to combine data from multiple sources to answer more complex business questions.
  • Understand different types of JOINs and when to use each type
    		•
    SQL AGGREGATIONS
  • Write common aggregations in SQL including COUNT, SUM, MIN, and MAX
  • Write CASE and DATE functions, as well as work with NULLs.

    • Course 2: Introduction to Python Programming

    In this part, you’ll learn to represent and store data using Python data types and variables, and use conditionals and loops to control the flow of your programs. You’ll harness the power of complex data structures like lists, sets, dictionaries, and tuples to store collections of related data. You’ll define and document your own custom functions, write scripts, and handle errors. You will also learn to use two powerful Python libraries - Numpy, a scientific computing package, and Pandas, a data manipulation package.

    Lesson Title Learning Outcomes
    WHY PYTHON PROGRAMMING
  • Gain an overview of what you’ll be learning and doing in the course.
  • Understand why you should learn programming with Python.
    		•
    DATA TYPES AND
  • Represent data using Python’s data types: integers, floats, Booleans, strings, lists, tuples, sets, dictionaries, compound data structures.
    • OPERATORS
  • Perform computations and create logical statements using Python’s operators: Arithmetic, Assignment, Comparison, Logical, Membership, and Identity
  • Declare, assign, and reassign values using Python variables.
  • Modify values using built-in functions and methods.
  • Practice whitespace and style guidelines.
    		•
    CONTROL FLOW
  • Write conditional expressions using if statements and Boolean expressions to add decision making to your Python programs.
  • Use for and while loops along with useful built-in functions to iterate over and manipulate lists, sets, and dictionaries.
  • Skip iterations in loops using break and continue
  • Condense for loops to create lists efficiently with list comprehensions.
    		•
    FUNCTIONS
  • Define your own custom functions.
  • Create and reference variables using the appropriate scope.
  • Add documentation to functions using doc-strings.
  • Define lambda expressions to quickly create anonymous functions.
  • Use iterators and generators to create streams of data.
    		•
    SCRIPTING
  • Install Python 3 and set up your programming environment.
  • Run and edit python scripts.
  • Interact with raw input from users.
  • Identify and handle errors and exceptions in your code.
  • Open, read, and write to files.
  • Find and use modules in Python Standard Library and third-party libraries.
  • Experiment in the terminal using a Python Interpreter.
    		•
    NUMPY
  • Create, access, modify, and sort multidimensional NumPy arrays (ndarrays).
  • Load and save ndarrays.
  • Use slicing, boolean indexing, and set operations to select or change subsets of an ndarray.
  • Understand difference between a view and a copy of ndarray.
  • Perform element-wise operations on ndarrays.
  • Use broadcasting to perform operations on ndarrays of different sizes.
    		•
    PANDAS
  • Create, access, and modify the main objects in Pandas, Series and DataFrames.
  • Perform arithmetic operations on Series and DataFrames.
  • Load data into a DataFrame.
  • Deal with Not a Number (NaN) values
    		•
    PROJECT Exploratory Data Analysis (EDA)

    Course 3: Introduction to Version Control

    In this course, you will learn how to use version control and share your work with other people in the Data Science industry.

    Lesson Title Learning Outcomes
    SHELL WORKSHOP
  • The UNIX shell is a powerful tool for developers of all sorts. Get a quick introduction to the basics of using it on your computer.
    		•
    PURPOSE & TERMINOLOGY
  • Learn why developers use version control and discover ways you use version control in your daily life.
  • Get an overview of essential Git vocabulary.
  • Configure Git using the command line.
    		•
    CREATE A GIT REPO
  • Create your first Git repository with git init.
  • Copy an existing Git repository with git clone.
  • Review the current state of a repository with the powerful git status
    		•
    REVIEW A REPO’S HISTORY
  • Review a repo’s commit history git log.
  • Customize git log’s output using command line flags in order to reveal more (or less) information about each commit.
  • Use the git show command to display just one commit.
    		•
    ADD COMMITS TO A REPO
  • Master the Git workflow and make commits to an example project.
  • Use git diff to identify parts of a file that changed in a commit.
  • Mark files as “untracked” using .gitignore.
    		•
    TAGGING, BRANCHING, AND MERGING
  • Discover tagging, branching, and merging and organize your commits with tags and branches
  • Jump to particular tags and branches using git checkout.
  • Learn how to merge together changes on different branches and crush those pesky merge conflicts.
    		•
    UNDOING CHANGES
  • Learn how and when to edit or delete an existing commit.
  • Use git commit and amend flag to alter the last commit.
  • Use git reset and git revert to undo and erase commits
    		•
    PROJECT
  • Post your work on Github
    		•
    Instructor:

    Engr. Umair bin Mansoor

    Assistant Professor
    Electrical Engineering Dept.
    DHA Suffa University
    Email:Umair.mansoor@dsu.edu.pk
    linkedin.com/in/umairbinmansoor