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

Sponsored by Southeastern University

55,440 already enrolled

Get in-depth knowledge of a subject
4.6

(2,906 reviews)

Beginner level

Recommended experience

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

(2,906 reviews)

Beginner level

Recommended experience

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

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

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Specialization - 5 course series

Tools for Data Science

Course 118 hours4.5 (29,204 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. 

Python for Data Science, AI & Development

Course 225 hours4.6 (38,831 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.

Python Project for Data Science

Course 38 hours4.5 (4,346 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: Python Programming

Statistics for Data Science with Python

Course 414 hours4.5 (409 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: Data Analysis
Category: Probability & Statistics
Category: General Statistics
Category: Python Programming
Category: Mathematical Theory & Analysis
Category: Statistical Programming
Category: Data Visualization

Databases and SQL for Data Science with Python

Course 520 hours4.7 (20,686 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.

Instructors

Murtaza Haider
IBM
3 Courses41,388 learners
Romeo Kienzler
IBM
10 Courses701,332 learners

Offered by

IBM

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