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 +7 more

63,874 already enrolled

Included with Coursera Plus

Get in-depth knowledge of a subject
4.6

(3,175 reviews)

Beginner level

Recommended experience

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

(3,175 reviews)

Beginner level

Recommended experience

Flexible schedule
2 months, 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

Skills you'll gain

  • Category: Probability Distribution
  • Category: Jupyter
  • Category: Data Import/Export
  • Category: Descriptive Statistics
  • Category: Data Visualization
  • Category: Dashboard
  • Category: Statistical Analysis
  • Category: Pandas (Python Package)
  • Category: Statistical Hypothesis Testing
  • Category: Statistics
  • Category: Python Programming
  • Category: Data Analysis

Details to know

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Taught in English

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

Tools for Data Science

Tools for Data Science

Course 118 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: Machine Learning
Category: Data Visualization Software
Category: Git (Version Control System)
Category: Big Data
Category: Version Control
Category: Cloud Computing
Category: Query Languages
Category: Statistical Programming
Category: Other Programming Languages
Category: Application Programming Interface (API)
Category: Python Programming
Category: Data Science

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: Python Programming
Category: Data Structures
Category: Object Oriented Programming (OOP)
Category: NumPy
Category: Web Scraping
Category: JSON
Category: Pandas (Python Package)
Category: Automation
Category: Scripting
Category: Computer Programming
Category: Restful API
Category: Data Manipulation
Category: Jupyter
Category: Application Programming Interface (API)
Category: Data Analysis
Category: Data Processing
Category: Programming Principles
Category: Data Import/Export

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 Science
Category: Web Scraping
Category: Data Analysis
Category: Data Processing
Category: Data Visualization Software
Category: Matplotlib
Category: Data Collection
Category: Jupyter
Category: Dashboard
Category: Pandas (Python Package)

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

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: Data Manipulation
Category: Databases
Category: Jupyter
Category: Data Analysis
Category: Relational Databases
Category: Python Programming
Category: Transaction Processing
Category: Database Management
Category: Query Languages
Category: Database Design
Category: Stored Procedure

Earn a career certificate

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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

 
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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
Murtaza Haider
IBM
3 Courses48,773 learners
Romeo Kienzler
Romeo Kienzler
IBM
10 Courses767,623 learners

Offered by

IBM

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