IBM
Data Science Fundamentals with Python and SQL Specialization
64,502 enrolled
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.

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Get in-depth knowledge of a subject

(3,196 reviews)

Beginner level

Recommended experience

Flexible schedule
2 months at 10 hours a week
Earn a career credential
Share your expertise with employers
Get in-depth knowledge of a subject

(3,196 reviews)

Beginner level

Recommended experience

Flexible schedule
2 months at 10 hours a week
Earn a career credential
Share your expertise with employers

Overview

  • 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

What’s included

Shareable certificate

Add to your LinkedIn profile

Taught in English
55 practice exercises

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 - 5 course series

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: Machine Learning
Category: Application Programming Interface (API)
Category: GitHub
Category: Git (Version Control System)
Category: Data Science
Category: Data Visualization Software
Category: Collaborative Software
Category: Data Management
Category: Open Source Technology
Category: Restful API
Category: Data Visualization
Category: Query Languages
Category: Python Programming
Category: Computer Programming Tools
Category: Cloud API
Category: Data Analysis Software
Category: IBM Cloud
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: Pandas (Python Package)
Category: Web Scraping
Category: Python Programming
Category: Data Structures
Category: NumPy
Category: Object Oriented Programming (OOP)
Category: Data Manipulation
Category: Programming Principles
Category: Application Programming Interface (API)
Category: Computer Programming
Category: Data Import/Export
Category: Jupyter
Category: Data Collection
Category: Data Processing
Category: Data Analysis

What you'll learn

  • Play the role of a Data Scientist / Data Analyst working on a real project.

  • Demonstrate your Skills in Python - the language of choice for Data Science and Data Analysis.

  • Apply Python fundamentals, Python data structures, and working with data in Python.

  • Build a dashboard using Python and libraries like Pandas, Beautiful Soup and Plotly using Jupyter notebook.

Skills you'll gain

Category: Python Programming
Category: Data Manipulation
Category: Data Analysis
Category: Dashboard
Category: Web Scraping
Category: Data Science
Category: Data Structures
Category: Jupyter
Category: NumPy
Category: Pandas (Python Package)
Category: Interactive Data Visualization
Category: Data Processing
Category: Data Capture

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 Distribution
Category: Probability & Statistics
Category: Correlation Analysis
Category: Regression Analysis
Category: Probability
Category: Data Analysis
Category: Jupyter
Category: Plot (Graphics)
Category: Statistics
Category: Statistical Methods
Category: Histogram
Category: Pandas (Python Package)
Category: Data Science
Category: Data Visualization
Category: Matplotlib
Category: Statistical 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: Transaction Processing
Category: Stored Procedure
Category: Pandas (Python Package)
Category: Relational Databases
Category: Data Manipulation
Category: Query Languages
Category: Databases
Category: Data Analysis
Category: Database Management
Category: Database Management Systems
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

 
ACE Logo

This Specialization has ACE® recommendation. It is eligible for college credit at participating U.S. colleges and universities. Note: The decision to accept specific credit recommendations is up to each institution. 

Instructors

Murtaza Haider
IBM
3 Courses49,288 learners
Romeo Kienzler
IBM
10 Courses773,260 learners
Joseph Santarcangelo
IBM
35 Courses2,069,496 learners
Rav Ahuja
IBM
56 Courses4,044,616 learners

Offered by

IBM

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