This Course introduces you to the fundamentals of data science through practical examples and hands-on exercises. The course begins with key questions about data science, followed by a case study on data science methodology. You’ll then build a simple chatbot to understand project workflows and move into Python for data science—covering fundamentals, control structures, functions, nested data, list comprehensions, and assignments for practice. You’ll also work with NumPy and Pandas for data manipulation. The final section focuses on essential math—linear algebra, probability, and statistics—with emphasis on intuition and reasoning, including least squares and Bayesian methods.
By the end, you’ll have a solid grasp of data science methodology, Python tools, and mathematical foundations to apply in real-world projects.
Who should take this Course?
The Data Science Essentials Online Course is perfect for students, beginners in programming, and professionals from technical or non-technical backgrounds who want to build a strong foundation in data science. It is also ideal for software developers, analysts, and business professionals looking to learn essential concepts like data analysis, visualization, and machine learning to apply data-driven decision-making in their careers.
What you will learn
Examine frequent questions asked by passionate learners
Explore data science methodology with a healthcare insurance case study
Solve a system of linear equations
Define the idea of a vector space
Recognize the proper probability model for your use case
Compute a least-squares solution through pseudoinverse
Course Outline
Introduction to Data Science 101
Matching Activity - Match the Project to the Data Role
Introduction to Data Science
What a Data Scientist Does
Big Data
Data Mining
Machine Learning Versus Deep Learning
Advice to Data Scientists
Best Language for Data Science
What IS the Best Language for Data Science?
Python
SAS (Statistical Analysis System)
R
SQL
Data Science Methodology
Data Science Methodology/Process Introduction
Business Understanding
Data Understanding
Data Prep
Modelling
Evaluation
Deployment
Data Science Through Chatbot
Purpose of Chatbot Section
What is a Chatbot?
Signing Up for Watson Assistant
Creating a Name - Healthcare Service Chatbot
Intents
Entities
Suggestions for More Learning
Section Recap: Natural Language Processing, Machine Learning, and Use Cases
Libraries, APIs, Datasets
Libraries
APIs
Datasets
GitHub
Introduction to GitHub
Create a Repository
Create a Branch and Commit Changes
Pull Request and Merging Pull Request
Installation / Jupyter / Comments (Windows and MacOS/Jupyter Notebook)
Windows - Download Anaconda Distribution (Includes Python!)
Windows - Install Anaconda Distribution
Windows - Setting Up Environment
Windows - Opening Jupyter Notebook
MacOS - Anaconda Download and Install
MacOS - Conda Environment
MacOS - Jupyter Notebook
Jupyter Notebook Interface and Shortcuts
Introduction to Data Science in Python - Python Fundamentals
How to Use Markdown Cells (Adding Headers, Links, and Images)
Comments - Inline and Block Comments
Python Indentation
Writing Single and Multiple Lines of Code
Understanding Variables
Main Data Types and Creating Them (Integer, Float, String, List, Dictionary)
Lists - How to Use
Dictionaries - How to Use
Creating a Tuple
Tuple - How to Use
Creating a Set
Set - How to Use
Operators
Introduction to Data Science in Python - Decision and Looping Structures
Introducing Decision and Looping Structures
If Statement
Else Statement
Elif
For Loop
While Loop
Break and Continue Statements
Introduction to Data Science in Python - Python Functions
Introducing Functions
Functions - General Syntax
+1 Function
Fav Band Function
Celsius to Fahrenheit Function
Optional Return Statement (and Comparing It to Print Statement)
Defining a Function Versus Calling a Function
Practical/Real World Example: Function to Get Reddit Data
Lambda Introduction (Anonymous Functions)
Formal Function Versus Lambda for Splitting Strings
Introduction to Data Science - Nested Data, Iteration, and List Comprehension
Introducing you to Nested Data and Iteration
Simple Nested Example
Double Indexing
Assigning Values
List of Dicts and Dicts of Dicts Example
Nested Iteration - Iterating Through List of Lists
Defining List Comprehension and Syntax
List Comprehension - Simple Examples
List Comp as an Alternative to Loops
Practical/Real World Example - Using Common Mathematical Notation
Practical/Real World Example - Creating a Constrained ID
Activity: Building Intuition (Loops, Nested Data, Iteration, and List Comp)
Introduction to Data Science in Python - Learn NumPy
Introducing NumPy
Creating Our First NumPy Array
Shaping an Array (When You Know the Shape You Want)
Creating a Sequence of Integers and Floats
Element-Wise Operations
A Range with a Shape (Arrange Function with Reshape Function)
NumPy Indexing
NumPy Slicing
Indexing and Slicing with Breast Cancer Wisconsin Dataset
Delete Elements
Append
Insert Elements
Reshape -1 Feature
Flatten
Transpose
Concatenate
Splitting
Aggregate/Statistical Functions
Introduction to Data Science in Python - Pandas
Introducing Pandas
For SAS Programmers: Analogous Terms in Pandas (Python)
Using Series as Input into DataFrame
Comparing Series and DataFrame
Importing TSLA Dataset
Index-Based Selection (iloc)
Label-Based Selection (loc)
Conditional Selection
Summary Functions
Grouping (groupby)
Sorting
Checking Data Types and Converting
Dealing with Missing Values
Dropping Columns/Variables and Records/Rows
Renaming Columns/Variables and Records/Rows
Concat Function + Pop Quiz
Real-World Activity: Add New Columns and Predict Stock Movement
Introduction to Data Science in Python - Python Activity Solutions
Solution - Fill in Activity - Fundamentals
Solution - Fill in Activity - Looping and Functions
Solution - Fill in Activity - Nested and List Comprehension
Solution - Fill in Activity - NumPy
Essential Math for Data Science - Linear Algebra Made Easy
Linear Equation Definition
Forms of a Linear Equation
Systems of Linear Equations
Line and Plane
Aij Notation
System of Equations as a Matrix
System in Corresponding Forms
Row Echelon Form (Gaussian Elimination)
Reduced Row Echelon Form
Row Operations Rules
Row Operations Example (REF)
Visualizing Ax=b
General Formula - Matrix Vector Multiplication
Tips for Row Operations
Essential Math for Data Science - Mathematical Structures
Mathematical Structures
Abelian Groups and Fields
Vector Spaces 1
Vector Spaces - Concrete Example
Subspaces
Linear Combinations and Span
Is It in the Span?
Linear Independence
A Basis for a Vector Space
Dim of C(A) and N(A)
The Dimension of a Vector Space
Linear Maps
The Four Fundamental Subspaces
Adding Geometry to Vector Spaces
Orthogonal Projection - How to Derive Projection and Check for Orthogonality
Least Squares
Least Squares Through Pseudoinverse - with Python and SAS code
Essential Math for Data Science - Introduction to Probability
Probability Models and Axioms
Simple Counting
Discrete Example
Conditional Bayes
Conditional Example 1
Conditional Healthcare (Cancer) Example 2
Independence of Events (What It Means and Does Not Mean)
Permutations and Combinations
Essential Math for Data Science - Random Variables and Multiple Variables
Random Variables
Probability Mass Function and Discrete R.V.s
Expectation and Variance for Discrete Random Variables
Joint PMFs (Multiple Discrete Variables)
Continuous Random Variables
Continuous Random Variables and Probability Density Function
Continuous R.V. Example
Joint PDF Example - Banking
Cumulative Distribution Function (CDF)
Covariance, Correlation, and More on Variance
Law of Large Numbers (LLN)
Central Limit Theorem (CLT)
Essential Math for Data Science - Statistical Inference
