Overview
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Data Science is one of the hottest professions of the decade, and the demand for data scientists who can analyze data and communicate results to inform data driven decisions has never been greater. This Specialization from IBM will help anyone interested in pursuing a career in data science by teaching them fundamental skills to get started in this in-demand field.
The specialization consists of 5 self-paced online courses that will provide you with the foundational skills required for Data Science, including open source tools and libraries, Python, Statistical Analysis, SQL, and relational databases. You’ll learn these data science pre-requisites through hands-on practice using real data science tools and real-world data sets.
Upon successfully completing these courses, you will have the practical knowledge and experience to delve deeper in Data Science and work on more advanced Data Science projects.
No prior knowledge of computer science or programming languages required.
This program is ACE® recommended—when you complete, you can earn up to 8 college credits.
Syllabus
Course 1: Tools for Data Science
- Offered by IBM. In order to be successful in Data Science, you need to be skilled with using tools that Data Science professionals employ as ... Enroll for free.
Course 2: Python for Data Science, AI & Development
- Offered by IBM. Kickstart your learning of Python with this beginner-friendly self-paced course taught by an expert. Python is one of the ... Enroll for free.
Course 3: Python Project for Data Science
- Offered by IBM. This mini-course is intended to for you to demonstrate foundational Python skills for working with data. This course ... Enroll for free.
Course 4: Statistics for Data Science with Python
- Offered by IBM. This Statistics for Data Science course is designed to introduce you to the basic principles of statistical methods and ... Enroll for free.
Course 5: Databases and SQL for Data Science with Python
- Offered by IBM. Working knowledge of SQL (or Structured Query Language) is a must for data professionals like Data Scientists, Data Analysts ... Enroll for free.
- Offered by IBM. In order to be successful in Data Science, you need to be skilled with using tools that Data Science professionals employ as ... Enroll for free.
Course 2: Python for Data Science, AI & Development
- Offered by IBM. Kickstart your learning of Python with this beginner-friendly self-paced course taught by an expert. Python is one of the ... Enroll for free.
Course 3: Python Project for Data Science
- Offered by IBM. This mini-course is intended to for you to demonstrate foundational Python skills for working with data. This course ... Enroll for free.
Course 4: Statistics for Data Science with Python
- Offered by IBM. This Statistics for Data Science course is designed to introduce you to the basic principles of statistical methods and ... Enroll for free.
Course 5: Databases and SQL for Data Science with Python
- Offered by IBM. Working knowledge of SQL (or Structured Query Language) is a must for data professionals like Data Scientists, Data Analysts ... Enroll for free.
Courses
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In order to be successful in Data Science, you need to be skilled with using tools that Data Science professionals employ as part of their jobs. This course teaches you about the popular tools in Data Science and how to use them. You will become familiar with the Data Scientist’s tool kit which includes: Libraries & Packages, Data Sets, Machine Learning Models, Kernels, as well as the various Open source, commercial, Big Data and Cloud-based tools. Work with Jupyter Notebooks, JupyterLab, RStudio IDE, Git, GitHub, and Watson Studio. You will understand what each tool is used for, what programming languages they can execute, their features and limitations. This course gives plenty of hands-on experience in order to develop skills for working with these Data Science Tools. With the tools hosted in the cloud on Skills Network Labs, you will be able to test each tool and follow instructions to run simple code in Python, R, or Scala. Towards the end the course, you will create a final project with a Jupyter Notebook. You will demonstrate your proficiency preparing a notebook, writing Markdown, and sharing your work with your peers.
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Working knowledge of SQL (or Structured Query Language) is a must for data professionals like Data Scientists, Data Analysts and Data Engineers. Much of the world's data resides in databases. SQL is a powerful language used for communicating with and extracting data from databases. In this course you will learn SQL inside out- from the very basics of Select statements to advanced concepts like JOINs. You will: -write foundational SQL statements like: SELECT, INSERT, UPDATE, and DELETE -filter result sets, use WHERE, COUNT, DISTINCT, and LIMIT clauses -differentiate between DML & DDL -CREATE, ALTER, DROP and load tables -use string patterns and ranges; ORDER and GROUP result sets, and built-in database functions -build sub-queries and query data from multiple tables -access databases as a data scientist using Jupyter notebooks with SQL and Python -work with advanced concepts like Stored Procedures, Views, ACID Transactions, Inner & Outer JOINs through hands-on labs and projects You will practice building SQL queries, work with real databases on the Cloud, and use real data science tools. In the final project you’ll analyze multiple real-world datasets to demonstrate your skills.
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Kickstart your learning of Python with this beginner-friendly self-paced course taught by an expert. Python is one of the most popular languages in the programming and data science world and demand for individuals who have the ability to apply Python has never been higher. This introduction to Python course will take you from zero to programming in Python in a matter of hours—no prior programming experience necessary! You will learn about Python basics and the different data types. You will familiarize yourself with Python Data structures like List and Tuples, as well as logic concepts like conditions and branching. You will use Python libraries such as Pandas, Numpy & Beautiful Soup. You’ll also use Python to perform tasks such as data collection and web scraping with APIs. You will practice and apply what you learn through hands-on labs using Jupyter Notebooks. By the end of this course, you’ll feel comfortable creating basic programs, working with data, and automating real-world tasks using Python. This course is suitable for anyone who wants to learn Data Science, Data Analytics, Software Development, Data Engineering, AI, and DevOps as well as a number of other job roles.
Taught by
Aije Egwaikhide, Hima Vasudevan, Joseph Santarcangelo, Murtaza Haider, Rav Ahuja, Romeo Kienzler and Svetlana Levitan