IBM
Data Science Fundamentals with Python and SQL Specialization
IBM

Data Science Fundamentals with Python and SQL Specialization

Build the Foundation for your Data Science career. Develop hands-on experience with Jupyter, Python, SQL. Perform Statistical Analysis on real data sets.

Murtaza Haider
Romeo Kienzler
Joseph Santarcangelo

Instructors: Murtaza Haider

Access provided by INFOMEDIA SA DE CV

66,062 already enrolled

Get in-depth knowledge of a subject
4.6

(3,228 reviews)

Beginner level

Recommended experience

Flexible schedule
2 months at 10 hours a week
Learn at your own pace
Build toward a degree
Get in-depth knowledge of a subject
4.6

(3,228 reviews)

Beginner level

Recommended experience

Flexible schedule
2 months at 10 hours a week
Learn at your own pace
Build toward a degree

What you'll learn

  • Working knowledge of Data Science Tools such as Jupyter Notebooks, R Studio, GitHub, Watson Studio

  • Python programming basics including data structures, logic, working with files, invoking APIs, and libraries such as Pandas and Numpy

  • Statistical Analysis techniques including Descriptive Statistics, Data Visualization, Probability Distribution, Hypothesis Testing and Regression

  • Relational Database fundamentals including SQL query language, Select statements, sorting & filtering, database functions, accessing multiple tables

Details to know

Shareable certificate

Add to your LinkedIn profile

Taught in English

See how employees at top companies are mastering in-demand skills

 logos of Petrobras, TATA, Danone, Capgemini, P&G and L'Oreal

Advance your subject-matter expertise

  • Learn in-demand skills from university and industry experts
  • Master a subject or tool with hands-on projects
  • Develop a deep understanding of key concepts
  • Earn a career certificate from IBM

Specialization - 4 course series

Tools for Data Science

Tools for Data Science

Course 13 hours

What you'll learn

  • Describe the Data Scientist’s tool kit which includes: Libraries & Packages, Data sets, Machine learning models, and Big Data tools 

  • Utilize languages commonly used by data scientists like Python, R, and SQL 

  • Demonstrate working knowledge of tools such as Jupyter notebooks and RStudio and utilize their various features  

  • Create and manage source code for data science using Git repositories and GitHub. 

Skills you'll gain

Category: Jupyter
Category: R Programming
Category: GitHub
Category: Data Visualization Software
Category: Machine Learning
Category: Git (Version Control System)
Category: IBM Cloud
Category: Python Programming
Category: Other Programming Languages
Category: Open Source Technology
Category: R (Software)
Category: Version Control
Category: Big Data
Category: Computer Programming Tools
Category: Data Science
Category: Query Languages
Category: Cloud Computing
Category: Development Environment
Category: Statistical Programming

What you'll learn

  • Develop a foundational understanding of Python programming by learning basic syntax, data types, expressions, variables, and string operations.

  • Apply Python programming logic using data structures, conditions and branching, loops, functions, exception handling, objects, and classes.

  • Demonstrate proficiency in using Python libraries such as Pandas and Numpy and developing code using Jupyter Notebooks.

  • Access and extract web-based data by working with REST APIs using requests and performing web scraping with BeautifulSoup.

Skills you'll gain

Category: Web Scraping
Category: Python Programming
Category: NumPy
Category: Data Structures
Category: Pandas (Python Package)
Category: Restful API
Category: Jupyter
Category: Programming Principles
Category: Data Manipulation
Category: Object Oriented Programming (OOP)
Category: Application Programming Interface (API)
Category: File Management
Category: Computer Programming
Category: Data Analysis

What you'll learn

  • Write Python code to conduct various statistical tests including a T test, an ANOVA, and regression analysis.

  • Interpret the results of your statistical analysis after conducting hypothesis testing.

  • Calculate descriptive statistics and visualization by writing Python code.

  • Create a final project that demonstrates your understanding of various statistical test using Python and evaluate your peer's projects.

Skills you'll gain

Category: Statistical Hypothesis Testing
Category: Descriptive Statistics
Category: Probability & Statistics
Category: Probability Distribution
Category: Probability
Category: Regression Analysis
Category: Correlation Analysis
Category: Jupyter
Category: Pandas (Python Package)
Category: Statistics
Category: Data Analysis
Category: Data Visualization
Category: Matplotlib
Category: Statistical Analysis
Category: Data Science
Category: Exploratory Data Analysis

What you'll learn

  • Analyze data within a database using SQL and Python.

  • Create a relational database and work with multiple tables using DDL commands.

  • Construct basic to intermediate level SQL queries using DML commands.

  • Compose more powerful queries with advanced SQL techniques like views, transactions, stored procedures, and joins.

Skills you'll gain

Category: SQL
Category: Pandas (Python Package)
Category: Jupyter
Category: Relational Databases
Category: Data Manipulation
Category: Databases
Category: Data Analysis
Category: Query Languages
Category: Stored Procedure
Category: Transaction Processing
Category: Python Programming

Earn a career certificate

Add this credential to your LinkedIn profile, resume, or CV. Share it on social media and in your performance review.

Build toward a degree

When you complete this Specialization, you may be able to have your learning recognized for credit if you are admitted and enroll in one of the following online degree programs.¹

 

Instructors

Murtaza Haider
IBM
3 Courses50,790 learners

Offered by

IBM

Why people choose Coursera for their career

Felipe M.
Learner since 2018
"To be able to take courses at my own pace and rhythm has been an amazing experience. I can learn whenever it fits my schedule and mood."
Jennifer J.
Learner since 2020
"I directly applied the concepts and skills I learned from my courses to an exciting new project at work."
Larry W.
Learner since 2021
"When I need courses on topics that my university doesn't offer, Coursera is one of the best places to go."
Chaitanya A.
"Learning isn't just about being better at your job: it's so much more than that. Coursera allows me to learn without limits."
Coursera Plus

Open new doors with Coursera Plus

Unlimited access to 10,000+ world-class courses, hands-on projects, and job-ready certificate programs - all included in your subscription

Advance your career with an online degree

Earn a degree from world-class universities - 100% online

Join over 3,400 global companies that choose Coursera for Business

Upskill your employees to excel in the digital economy