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This IBM Data Science Professional Certificate has a strong emphasis on applied learning. Except for the first course, all other courses include a series of hands-on labs on the IBM Cloud that will give you practical skills with applicability to real jobs, including: Tools: Jupyter/JupyterLab, GitHub, R Studio, and Watson Studio Libraries: Pandas, NumPy , Matplotlib, Seaborn, Folium, ipython-sql, Scikit-learn, ScipPy, etc. Projects: Random Album Generator, Home Price Prediction, Best Classifier Model, Neighborhood Battle.
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 IBM Data Science Professional Certificate will help anyone interested in pursuing a career in data science or machine learning develop career-relevant skills and experience.
It is a myth that to become a data scientist you need a Ph.D. Anyone with a passion for learning can take this Professional Certificate (no prior knowledge of computer science or programming languages required) and develop the skills, tools, and portfolio to have a competitive advantage in the job market as an entry-level data scientist. .
The program consists of 9 online courses that will provide you with the latest job-ready tools and skills, including open source tools and libraries, Python, Databases, SQL, Data Visualization, Data Analysis, Statistical Analysis, Predictive Modeling and machine learning algorithms. . You'll learn data science through hands-on practice on the IBM Cloud using real data science tools and real-world data sets.
Upon successful completion of these courses, you will have built a portfolio of data science projects to give you the confidence to dive into an exciting career in data science.
In addition to earning a Coursera Professional Certificate, you'll also receive a digital badge from IBM that recognizes your data science competency.
The art of uncovering insights and trends from data has been around since ancient times. The ancient Egyptians used census data to increase efficiency in tax collection and accurately predicted the flooding of the Nile River each year. Since then, people who work in data science have carved out a unique and distinct field for the work they do. This field is data science.
In this course, we'll meet some data science professionals and get an overview of what data science is today.
What are some of the most popular data science tools, how do you use them, and what are their features? In this course, you will learn about Jupyter Notebooks, RStudio IDE, Apache Zeppelin, and Data Science Experience. You will learn what each tool is used for, what programming languages they can run, their features and limitations.
With the cloud-hosted tools at Cognitive Class Labs, you can try each tool and follow the instructions to run simple code in Python, R, or Scala. To complete the course, you'll create a capstone project using a Jupyter Notebook in the IBM Data Science Experience and demonstrate your proficiency by preparing a notebook, writing Markdown, and sharing your work with your peers.
LIMITED TIME OFFER: Subscription is only $39 USD per month for access to qualifying materials and a certificate.
Check if this offer is valid on the Coursera portal.
Despite the recent increase in computing power and access to data over the last two decades, our ability to use data in the decision-making process is too often lost or not maximized, we do not have a solid understanding of the questions being asked and how to apply the data correctly to the problem at hand.
This course has one purpose, and that is to share a methodology that can be used within data science, to ensure that the data used in problem solving is relevant and appropriately manipulated to address the question at hand. Consequently, in this course, you will learn: - The main steps required to tackle a data science problem. - The main steps involved in the practice of data science, from forming a concrete business or research problem, to collecting and analyzing data, and building a model. and understand feedback after model deployment. - How data scientists think!
LIMITED TIME OFFER: Subscription is only $39 USD per month for access to qualifying materials and a certificate.
Check if this offer is valid on the Coursera portal.
Jump-start your learning of Python for data science, as well as programming in general, with this introduction to Python for beginners. Python is one of the most popular programming languages in the world, and there has never been a greater demand for professionals with the ability to apply Python fundamentals to power business solutions across industries.
This course will take you from scratch to programming in Python in a matter of hours, no prior programming experience necessary! You'll learn the fundamentals of Python, including data structures and data analysis, complete hands-on exercises throughout the course modules, and create a capstone project to demonstrate your new skills. By the end of this course, you will be comfortable creating basic programs, working with data, and solving real-world problems in Python. He will gain a solid foundation for further learning in the field and develop skills to help advance his career. This course can be applied to multiple specialization or professional certificate programs.
Completion of this course will count toward your learning in any of the following programs: IBM Applied AI Professional Certificate Applied Data Science Specialization IBM Data Science Professional Certificate Upon completion of any of the above programs, in addition to earning a certificate of completion coursera specialization, you will also receive a digital badge from IBM that recognizes your expertise in the field.
Much of the world's data resides in databases. SQL (or Structured Query Language) is a powerful language used to communicate with and extract data from databases. A working knowledge of databases and SQL is a must if you want to become a data scientist.
The purpose of this course is to introduce relational database concepts and help you learn and apply basic knowledge of the SQL language. It is also intended to help you get started with performing SQL access in a data science environment. The emphasis in this course is on hands-on, hands-on learning. As such, you'll work with real databases, real data science tools, and real-world data sets. You will create a database instance in the cloud. Through a series of labs, you will practice creating and executing SQL queries. You will also learn how to access databases from Jupyter notebooks using SQL and Python.
No prior knowledge of databases, SQL, Python, or programming is required. Anyone can audit this course free of charge. If you choose to take this course and earn the Coursera course certificate, you can also earn an IBM digital badge upon successful completion of the course.
LIMITED TIME OFFER: Subscription is only $39 USD per month for access to qualifying materials and a certificate.
Check if this offer is valid on the Coursera portal.
Learn to analyze data with Python. This course will take you from the basics of Python to exploring many different types of data.
You'll learn how to prepare data for analysis, perform simple statistical analysis, create meaningful data visualizations, predict future trends from data, and more!
Topics covered:
Data Analysis with Python will be delivered through lectures, labs, and assignments. It includes the following parts: Data Analysis Libraries - You will learn how to use the Pandas, Numpy, and Scipy libraries to work with a sample data set. We'll introduce you to pandas, an open source library, and use it to load, manipulate, analyze, and visualize interesting data sets. Then we'll introduce you to another open source library, scikit-learn, and use some of its machine learning algorithms to build smart models and make interesting predictions.
If you choose to take this course and earn the Coursera course certificate, you will also earn an IBM digital badge.
LIMITED TIME OFFER: Subscription is only $39 USD per month for access to qualifying materials and a certificate.
Check if this offer is valid on the Coursera portal.
"A picture is worth a thousand words". We are all familiar with this expression. It is especially applicable when trying to explain the information obtained from the analysis of ever larger data sets. Data visualization plays an essential role in representing data on both a small and large scale.
One of the key skills of a data scientist is the ability to tell a compelling story, visualizing data and findings in an accessible and thought-provoking way. Learning to take advantage of a software tool to visualize data will also allow you to extract insights, better understand the data, and make more effective decisions.
The main goal of this Data Visualization with Python course is to teach you how to take data that at first glance has little meaning and present it in a way that makes sense to people. Several techniques have been developed to present data visually, but in this course we will use several Python data visualization libraries, namely Matplotlib, Seaborn, and Folium.
LIMITED TIME OFFER: Subscription is only $39 USD per month for access to qualifying materials and a certificate.
Check if this offer is valid on the Coursera portal.
This course dives into the basics of machine learning using a familiar and accessible programming language, Python. In this course, we'll review two main components: First, you'll learn about the purpose of machine learning and where it applies to the real world. Second, you'll get an overview of machine learning topics such as supervised versus unsupervised learning, model evaluation, and machine learning algorithms.
In this course, you'll practice with real-life examples of machine learning and see how it affects society in ways you may not have guessed.
By just putting in a few hours a week for the next few weeks, here's what you'll get:
If you choose to take this course and earn the Coursera course certificate, you will also earn an IBM digital badge upon successful completion of the course.
With a Coursera Professional Certificate you could start a new career or change your current career. Today's world is demanding skills and knowledge in technologies that more and more companies need. Learn at your own pace, when and where you want. In a period of less than a year you could acquire a professional certificate, which added to your current profession, could give you substantial added value to your work experience and attract the attention of "head hunters".
The most prestigious universities and the most relevant companies in the world offer professional certificates in alliance with Coursera
Professional certificates are the best way to receive top quality education in the world, at unique values.
Each study offers certification options highly valued by recruiters, or prepare you for official industry certification.
Professional certificates are in-depth studies in high-demand technology skills that you can earn in about 6-10 months.
Coursera offers courses from over 200 leading universities and companies to deliver online learning around the world. With a Coursera Plus subscription, you get unlimited access to over 90% of all courses, and the most popular professional certificates and specializations on Coursera.
Data science, business and personal development. You can enroll in multiple courses at once, earn unlimited certificates, and learn in-demand job skills to start, grow, and even change careers.
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Ph.D., Data Scientist
IBM Developer Skills Network
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IBM offers a wide range of consulting and technology services; a broad portfolio of middleware for collaboration, predictive analytics, software development, and systems management; and the most advanced servers and supercomputers in the world. Using its R&D, technology and business consulting expertise, IBM helps clients become "smarter" as the planet becomes more digitally interconnected. IBM spends more than $6 billion a year on R&D, and just completed its 5st year of patent leadership. IBM Research has received recognition beyond any commercial technology research organization and is home to 9 Nobel Laureates, 5 US National Medals of Technology, 6 US National Medals of Science, 10 Turing Awards and XNUMX inductees of the US Inventors Hall of Fame
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