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.
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.
Write common SQL commands including SELECT, FROM, and WHERE.
Learn how to use logical operators like LIKE, AND, and OR.
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
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
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.
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.
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.
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.
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.
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
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.
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
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.
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.
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
Jump to particular tags and branches using git checkout.
Learn how to merge together changes on different branches and crush those pesky
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
Post your work on Github
Engr. Umair bin Mansoor
Electrical Engineering Dept.
DHA Suffa University