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

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60,335 already enrolled

Get in-depth knowledge of a subject
4.6

(3,080 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

(3,080 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

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
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Specialization - 5 course series

Tools for Data Science

Course 118 hours4.5 (29,670 ratings)

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: R Programming
Category: SQL
Category: GitHub
Category: Jupyter
Category: Data Visualization Software
Category: Application Programming Interface (API)
Category: Python Programming
Category: Git (Version Control System)
Category: Machine Learning
Category: Data Science
Category: Big Data
Category: Cloud Computing
Category: Statistical Programming

Python for Data Science, AI & Development

Course 225 hours4.6 (40,475 ratings)

What you'll learn

  • Learn Python - the most popular programming language and for Data Science and Software Development.

  • Apply Python programming logic Variables, Data Structures, Branching, Loops, Functions, Objects & Classes.

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

  • Access and web scrape data using APIs and Python libraries like Beautiful Soup.

Skills you'll gain

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

Python Project for Data Science

Course 38 hours4.5 (4,559 ratings)

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

Statistics for Data Science with Python

Course 414 hours4.5 (431 ratings)

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

Databases and SQL for Data Science with Python

Course 520 hours4.7 (21,592 ratings)

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: Data Analysis
Category: Stored Procedure
Category: Relational Databases
Category: Pandas (Python Package)
Category: Query Languages
Category: Jupyter
Category: Databases
Category: Database Management
Category: Database Design
Category: Data Manipulation

Instructors

Murtaza Haider
IBM
3 Courses45,593 learners
Romeo Kienzler
IBM
10 Courses736,717 learners

Offered by

IBM

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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Degree credit eligible

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.

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