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Unlock Free Data Science Courses from IBM Today!

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Chapter 1: Introduction to Free Online Learning

IBM has launched a series of complimentary online courses aimed at those interested in delving into data science. Whether you're a complete novice or looking to enhance your skills, these courses offer a solid foundation for your data science journey.

Section 1.1: Python Fundamentals for Data Science

The Python course is tailored for beginners eager to learn programming for data science applications. It encompasses the essentials of Python, such as variable definition, conditional statements, functions, and file handling for data input and output. Additionally, the course introduces the pandas library, which is vital for data analysis.

By the end of this course, participants will be able to craft their own Python scripts and execute basic data analyses within a Jupyter lab environment. This program is ideal for anyone wishing to start their Python learning journey and embark on personal data science projects. Moreover, learners can earn a skill badge upon completion to showcase their newfound expertise.

IBM offers free online courses in data science, perfect for beginners.

Section 1.2: Data Analytics Essentials for All

This course focuses on the core concepts of data analytics, a crucial component of data science. It dives into the data analytics lifecycle, the overall data ecosystem, and the various roles in the field, including Data Engineer, Data Analyst, Data Scientist, Business Analyst, and Business Intelligence Analyst.

Participants will explore diverse data structures, file formats, and sources of data while gaining insights into data repositories, the ETL process, and Big Data platforms. The course also covers the tools and techniques employed by Data Analysts for data gathering, wrangling, mining, analysis, and visualization. By the end of the course, learners will understand various career paths in data analytics and the different educational routes available.

Chapter 2: SQL and R Programming for Data Science

Section 2.1: SQL for Data Science

Focusing on SQL, this course equips learners with the skills necessary to interact with and extract information from databases—a must-have for professionals in data science and machine learning. Through practical exercises, participants will work with real databases, developing and executing SQL queries.

The course emphasizes hands-on learning, requiring no prior experience in databases, SQL, or programming. By the conclusion, participants will possess a foundational understanding of SQL, including how to create databases, query data, and analyze it using Python.

Section 2.2: R Programming Basics for Data Science

In this course, participants will familiarize themselves with the R programming language, widely utilized in data analysis. Covering data types, structures, and programming techniques, this course emphasizes practical skills, allowing learners to manipulate data effectively.

No prior knowledge of R is necessary. By the end of the course, learners will be capable of manipulating various data formats, controlling program flow, defining functions, and performing operations on both numeric and textual data.

Explore the top 10 data courses you should take in 2024, featuring Google and IBM certifications.

Section 2.3: Introduction to AI: Mastering the Basics

This course serves as an excellent introduction to Artificial Intelligence (AI) for individuals with little or no background in the field. It covers fundamental AI concepts, including applications, machine learning, deep learning, and neural networks. Ethical considerations and the societal impact of AI will also be discussed.

Designed for learners from all backgrounds, no programming or computer science experience is required. By the end, students will have a clearer understanding of AI's role in our lives and guidance on pursuing a career in the field, along with a mini project to showcase their comprehension of AI in practice.

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