Overview
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This action-packed Specialization is for data science enthusiasts who want to acquire practical skills for real world data problems. If you’re interested in pursuing a career in data science, and already have foundational skills or have completed the Introduction to Data Science Specialization, this program is for you! This 4-course Specialization will give you the tools you need to analyze data and make data driven business decisions leveraging computer science and statistical analysis. You will learn Python–no prior programming knowledge necessary–and discover methods of data analysis and data visualization. You’ll utilize tools used by real data scientists like Numpy and Pandas, practice predictive modeling and model selection, and learn how to tell a compelling story with data to drive decision making. Through guided lectures, labs, and projects in the IBM Cloud, you’ll get hands-on experience tackling interesting data problems from start to finish. Take this Specialization to solidify your Python and data science skills before diving deeper into big data, AI, and deep learning. In addition to earning a Specialization completion certificate from Coursera, you’ll also receive a digital badge from IBM. This Specialization can also be applied toward the IBM Data Science Professional Certificate. This program is ACE® recommended—when you complete, you can earn up to 12 college credits.
Syllabus
Course 1: 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 2: 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 3: Data Analysis with Python
- Offered by IBM. Analyzing data with Python is an essential skill for Data Scientists and Data Analysts. This course will take you from the ... Enroll for free.
Course 4: Data Visualization with Python
- Offered by IBM. One of the most important skills of successful data scientists and data analysts is the ability to tell a compelling story ... Enroll for free.
Course 5: Applied Data Science Capstone
- Offered by IBM. This is the final course in the IBM Data Science Professional Certificate as well as the Applied Data Science with Python ... Enroll for free.
- 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 2: 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 3: Data Analysis with Python
- Offered by IBM. Analyzing data with Python is an essential skill for Data Scientists and Data Analysts. This course will take you from the ... Enroll for free.
Course 4: Data Visualization with Python
- Offered by IBM. One of the most important skills of successful data scientists and data analysts is the ability to tell a compelling story ... Enroll for free.
Course 5: Applied Data Science Capstone
- Offered by IBM. This is the final course in the IBM Data Science Professional Certificate as well as the Applied Data Science with Python ... Enroll for free.
Courses
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Analyzing data with Python is an essential skill for Data Scientists and Data Analysts. This course will take you from the basics of data analysis with Python to building and evaluating data models. Topics covered include: - collecting and importing data - cleaning, preparing & formatting data - data frame manipulation - summarizing data - building machine learning regression models - model refinement - creating data pipelines You will learn how to import data from multiple sources, clean and wrangle data, perform exploratory data analysis (EDA), and create meaningful data visualizations. You will then predict future trends from data by developing linear, multiple, polynomial regression models & pipelines and learn how to evaluate them. In addition to video lectures you will learn and practice using hands-on labs and projects. You will work with several open source Python libraries, including Pandas and Numpy to load, manipulate, analyze, and visualize cool datasets. You will also work with scipy and scikit-learn, to build machine learning models and make predictions. If you choose to take this course and earn the Coursera course certificate, you will also earn an IBM digital badge.
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Visualizing data is used by virtually every discipline these days. It is used for analyzing web traffic to determine peak server load, growth and death rate of populations for biological analysis, analyzing weather patterns over time, stock market trends, and so on. Simply put, Data Visualization brings meaning to numbers that help people understand it. Seeing the data change can draw attention to trends and spikes that may otherwise go unnoticed. Python is an open-source (free) programming language has libraries that can be used to read and make useful graphics to present the data. In this course, you will create an application that reads data from CSV files. You will learn how to visualize the data using various techniques using existing Python libraries. Note: This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.
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This is the final course in the IBM Data Science Professional Certificate as well as the Applied Data Science with Python Specialization. This capstone project course will give you the chance to practice the work that data scientists do in real life when working with datasets. In this course you will assume the role of a Data Scientist working for a startup intending to compete with SpaceX, and in the process follow the Data Science methodology involving data collection, data wrangling, exploratory data analysis, data visualization, model development, model evaluation, and reporting your results to stakeholders. You will be tasked with predicting if the first stage of the SpaceX Falcon 9 rocket will land successfully. With the help of your Data Science findings and models, the competing startup you have been hired by can make more informed bids against SpaceX for a rocket launch. In this course, there will not be much new learning, instead you’ll focus on hands-on work to demonstrate and apply what you have learnt in previous courses. By successfully completing this Capstone you will have added a project to your data science and machine learning portfolio to showcase to employers.
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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
Alex Aklson and Joseph Santarcangelo