Data Science Professional Certificate by IBM
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The specialization is made up of nine modules that will teach you the most up-to-date job-ready tools and skills, such as open source tools and libraries, Python, databases, SQL, visualisation and analysis of data, statistical analysis, predictive modelling, and machine learning algorithms. You will experience learning data science through hands-on practice in the IBM Cloud with real data science tools and data sets. Anyone with a desire to learn can enrol in this Professional Certificate without any prior knowledge of computer science or programming languages. This IBM Professional Certificate will assist anyone who wants to pursue a career in data science to develop skills, tools, and portfolio necessary to compete in the job market as a data scientist.
Topics for this course:
What is Data Science
We will meet some data science practitioners and get an overview of what data science is today in this module.
Tools for Data Science
In this module you will learn what are the most popular tools for data science and discover, how do you use them, what each tool is used for, and what features do they have?
Data Science Methodology
In this module you will learn what data scientists think about! What are the major steps in approaching a data science problem?
Guided Project 1: Statistics For Data Science
In this project you will get hands-on experience on how to use statistics in data science.
Python for Data Science, AI & Development
This course will take you from scratch to Python programming even if you have no prior programming experience. You will complete hands-on exercises throughout the course modules and create a final project to demonstrate your new skills.
Guided Project 2: Python for Data Analysis: Pandas & NumPy
In this hands-on project, we will learn the fundamentals of data analysis in Python and use the power of two important Python libraries, Numpy and pandas which are two of the most popular Python libraries used in data science.
Python Project for Data Science
In this module you are required to work on a hands-on project in which you will create a simple dashboard in Python by demonstrating Python fundamental data-working skills.
Guided Project 3: COVID19 Data Analysis Using Python
You will learn how to preprocess and merge datasets in order to calculate required measures and prepare them for analysis in this project. In this project, we will use the COVID19 dataset, which was published by John Hopkins University.
Databases and SQL for Data Science with Python
This module places a strong emphasis on hands-on and practical learning. You will practise building and running SQL queries through a series of hands-on labs. You will also learn how to use SQL and Python to access databases from Jupyter notebooks.
Data Analysis with Python
This module will teach you how to prepare and analyze data using Python. You will learn how to conduct basic statistical analysis and create meaningful visualizations of data, forecast future trends, and much more.
Data Visualization with Python
The purpose of the Data Visualization with Python course is to teach you how to take data that appears to have little meaning at first glance and present it in a way that people can understand.
Machine learning with Python
This module will give you an overview of machine learning topics and you will practise with real world examples of machine learning.
Applied Data Science Capstone
In this final project you will get the taste of what data scientists go through when working with real datasets in the real world. In this module you will be following Data Science methodology and reporting your results to stakeholders
Global Program Director
Rav Ahuja works as a Global Program Director for IBM. He designed the IBM Data Science Professional Certificate and teaches the Databases & SQL for Data Science course on Coursera.
Ph.D., Data Scientist at IBM
Joseph holds a Ph.D. in Electrical Engineering, and his research focused on determining how videos affect human cognition using machine learning, signal processing, and computer vision. Joseph has been with IBM since completing his PhD.
Chief Data Scientist, Course Lead
Romeo Kienzler has a Master of Science (ETH) in Information Systems, Bioinformatics, and Applied Statistics (Swiss Federal Institute of Technology). He has nearly two decades of experience in the fields of software engineering, database administration, and information integration. He has been employed by IBM as a Data Scientist since 2012.
Senior Data SCientist
Aije Egwaikhide is currently employed by IBM, where she began her career as a Junior Data Scientist in the Global Business Services (GBS) division in 2018. Her primary responsibility was to make sense of data for their Oil and Gas clients using basic statistics and advanced Machine Learning algorithms.
Hima Vasudevan works as a Data Scientist in IBM’s Digital Business Group. She is a member of the Cognitive Class team, where she is responsible for developing skill offerings and delivering learning curriculum for the Data Science and Data Engineering professions.
Ph.D., Sr. Data Scientist
Saeed Aghabozorgi, PhD works for IBM as a Senior Data Scientist. He is a data mining researcher and specialized in the development of advanced analytic methods such as deep learning, machine learning, and statistical modelling on large datasets.
Ph.D., Data Scientist
Alex Aklson, Ph.D., is a data scientist in IBM Canada’s Digital Business Group. The University of Toronto awarded Alex a Ph.D. in Biomedical Engineering.
Data Scientist and Developer Advocate
Saishruthi Swaminathan is a data scientist and developer advocate on the IBM CODAIT team, with the goal of democratising data and AI through open source technologies. iative, as well as organising meetups centred on women’s empowerment.
Cognitive Data Scientist
Azim Hirjani is a cognitive Data SCientist at IBM.
Polong works at IBM as a Data Scientist, focusing on data science advocacy and partnerships. He co-founded an IBM Data Science Bootcamp and currently leads Canada’s largest data science meetup group in Toronto.
Senior Developer Advocate with IBM Center for Open Data and AI Technologies
Svetlana has been a software engineer and technical lead for SPSS for many years and is now a Senior Developer Advocate with IBM Center for Open Data and AI Technologies.
Ph.D., Data Scientist and Developer
Yan Luo, Ph.D., works at IBM Canada as a data scientist and developer. Yan has been developing innovative AI and cognitive applications in a variety of fields. Yan holds a Ph.D. in Machine Learning from the University of Western Ontario.
Instructor: Rav Ahuja +11 more instructors
Duration: 6 months
Skill level: Beginner level
Structure: 10 modules
Enrolled : 0 students