IBM
IBM Data Science Professional Certificate
IBM

IBM Data Science Professional Certificate

Kickstart your career in data science & ML. Build data science skills, learn Python & SQL, analyze & visualize data, build machine learning models. No degree or prior experience required.

Rav Ahuja
Alex Aklson
Aije Egwaikhide

Instructors: Rav Ahuja

192,887 already enrolled

Professional Certificate - 10 course series

Earn a career credential that demonstrates your expertise

4.6

(63,314 reviews)

Beginner level
No previous experience necessary
5 months at 10 hours a week
Flexible schedule
Learn at your own pace
Earn degree credit

What you'll learn

  • Describe what is data science, the various activities of a data scientist’s job, and methodology to think and work like a data scientist  

  • Develop hands-on skills using the tools, languages, and libraries used by professional data scientists  

  • Import and clean data sets, analyze and visualize data, and build and evaluate machine learning models and pipelines using Python 

  • Apply various data science skills, techniques, and tools to complete a project using a real-world data set and publish a report for stakeholders

Skills you'll gain

  • Category: Data Science
  • Category: Deep Learning
  • Category: Machine Learning
  • Category: Big Data
  • Category: Data Mining
  • Category: Github
  • Category: Python Programming
  • Category: Jupyter notebooks
  • Category: Rstudio
  • Category: Methodology
  • Category: CRISP-DM
  • Category: Data Analysis
  • Category: Pandas
  • Category: Numpy
  • Category: Cloud Databases
  • Category: Relational Database Management System (RDBMS)
  • Category: SQL
  • Category: Predictive Modelling
  • Category: Data Visualization (DataViz)
  • Category: Model Selection
  • Category: Dashboards and Charts
  • Category: dash
  • Category: Matplotlib
  • Category: SciPy and scikit-learn
  • Category: regression
  • Category: classification
  • Category: Hierarchical Clustering
  • Category: Jupyter Notebook
  • Category: Data Science Methodology
  • Category: K-Means Clustering

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Professional Certificate - 10 course series

Earn a career credential that demonstrates your expertise

4.6

(63,314 reviews)

Beginner level
No previous experience necessary
5 months at 10 hours a week
Flexible schedule
Learn at your own pace
Earn degree credit

See how employees at top companies are mastering in-demand skills

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Prepare for a career in Data Science

  • Receive professional-level training from IBM
  • Demonstrate your proficiency in portfolio-ready projects
  • Earn an employer-recognized certificate from IBM
  • Qualify for in-demand job titles: Data Scientist, Junior Data Scientist, Data Architect
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$130,000+
median U.S. salary for Data Science
¹
83,000+
U.S. job openings in Data Science
¹
71%
of certificate graduates report career improvement
²

Get exclusive access to career resources upon completion

  • Soft skills training

    Get free access to IBM’s People and Soft Skills Specialization

  • Resume review

    Improve your resume and LinkedIn with personalized feedback

  • Interview prep

    Practice your skills with interactive tools and mock interviews

  • Career support

    Plan your career move with Coursera’s job search guide

¹Lightcast™ Job Postings Report, United States, 1/1/22-12/31/22. ²Based on program graduate survey responses, United States 2021.

Professional Certificate - 10 course series

What is Data Science?

Course 19 hours4.7 (63,176 ratings)

What you'll learn

  • Define data science and its importance in today’s data-driven world.

  • Describe the various paths that can lead to a career in data science.

  • Summarize advice given by seasoned data science professionals to data scientists who are just starting out.

  • Explain why data science is considered the most in-demand job in the 21st century.

Skills you'll gain

Category: Data Science
Category: Deep Learning
Category: Machine Learning
Category: Big Data
Category: Data Mining

Tools for Data Science

Course 217 hours4.5 (26,501 ratings)

What you'll learn

  • Describe the Data Scientist’s tool kit which includes: Libraries & Packages, Data sets, Machine learning models, and Big Data tools 

  • Utilize languages commonly used by data scientists like Python, R, and SQL 

  • Demonstrate working knowledge of tools such as Jupyter notebooks and RStudio and utilize their various features  

  • Create and manage source code for data science using Git repositories and GitHub. 

Skills you'll gain

Category: Data Science
Category: Github
Category: Python Programming
Category: Jupyter notebooks
Category: Rstudio

Data Science Methodology

Course 38 hours4.6 (19,034 ratings)

What you'll learn

  • Describe what a methodology is and why data scientists need a methodology.

  • Apply the six stages in the Cross-Industry Process for Data Mining (CRISP-DM) methodology to analyze a case study. 

  • Determine an appropriate analytic model including predictive, descriptive, and classification models to analyze a case study.  

  • Decide on  appropriate sources of data for your data science project. 

Skills you'll gain

Category: Data Science
Category: Methodology
Category: CRISP-DM
Category: Data Analysis
Category: Data Mining

Python for Data Science, AI & Development

Course 422 hours4.6 (31,847 ratings)

What you'll learn

  • Describe Python Basics including Data Types, Expressions, Variables, and Data Structures.

  • Apply Python programming logic using Branching, Loops, Functions, Objects & Classes.

  • Demonstrate proficiency in using Python libraries such as Pandas, Numpy, and Beautiful Soup.

  • Access web data using APIs and web scraping from Python in Jupyter Notebooks.

Skills you'll gain

Category: Data Science
Category: Python Programming
Category: Data Analysis
Category: Pandas
Category: Numpy

Python Project for Data Science

Course 58 hours4.5 (3,179 ratings)

What you'll learn

  • Play the role of a Data Scientist / Data Analyst working on a real project.

  • Demonstrate your Skills in Python - the language of choice for Data Science and Data Analysis.

  • Apply Python fundamentals, Python data structures, and working with data in Python.

  • Build a dashboard using Python and libraries like Pandas, Beautiful Soup and Plotly using Jupyter notebook.

Skills you'll gain

Category: Data Science
Category: Python Programming
Category: Data Analysis
Category: Pandas
Category: Jupyter notebooks

Databases and SQL for Data Science with Python

Course 639 hours4.6 (17,629 ratings)

What you'll learn

  • Analyze data within a database using SQL and Python.

  • Create a relational database on Cloud and work with tables.

  • Write SQL statements including SELECT, INSERT, UPDATE, and DELETE.

  • Build more powerful queries with advanced SQL techniques like views, transactions, stored procedures and joins.

Skills you'll gain

Category: Cloud Databases
Category: Python Programming
Category: Jupyter notebooks
Category: Relational Database Management System (RDBMS)
Category: SQL

Data Analysis with Python

Course 714 hours4.7 (16,654 ratings)

What you'll learn

  • Develop Python code for cleaning and preparing data for analysis - including handling missing values, formatting, normalizing, and binning data

  • Perform exploratory data analysis and apply analytical techniques to real-word datasets using libraries such as Pandas, Numpy and Scipy

  • Manipulate data using dataframes, summarize data, understand data distribution, perform correlation and create data pipelines

  • Build and evaluate regression models using machine learning scikit-learn library and use them for prediction and decision making

Skills you'll gain

Category: Predictive Modelling
Category: Python Programming
Category: Data Analysis
Category: Data Visualization (DataViz)
Category: Model Selection

Data Visualization with Python

Course 817 hours4.5 (10,918 ratings)

What you'll learn

  • Implement data visualization techniques and plots using Python libraries, such as Matplotlib, Seaborn, and Folium to tell a stimulating story

  • Create different types of charts and plots such as line, area, histograms, bar, pie, box, scatter, and bubble

  • Create advanced visualizations such as waffle charts, word clouds, regression plots, maps with markers, & choropleth maps

  • Generate interactive dashboards containing scatter, line, bar, bubble, pie, and sunburst charts using the Dash framework and Plotly library

Skills you'll gain

Category: Dashboards and Charts
Category: dash
Category: Python Programming
Category: Matplotlib
Category: Data Visualization (DataViz)

Machine Learning with Python

Course 912 hours4.7 (14,080 ratings)

What you'll learn

  • Describe the various types of Machine Learning algorithms and when to use them 

  • Compare and contrast linear classification methods including multiclass prediction, support vector machines, and logistic regression 

  • Write Python code that implements various classification techniques including K-Nearest neighbors (KNN), decision trees, and regression trees 

  • Evaluate the results from simple linear, non-linear, and multiple regression on a data set using evaluation metrics 

Skills you'll gain

Category: SciPy and scikit-learn
Category: Machine Learning
Category: regression
Category: classification
Category: Hierarchical Clustering

Applied Data Science Capstone

Course 1017 hours4.7 (6,599 ratings)

What you'll learn

  • Demonstrate proficiency in data science and machine learning techniques using a real-world data set and prepare a report for stakeholders 

  • Apply your skills to perform data collection, data wrangling, exploratory data analysis, data visualization model development, and model evaluation

  • Write Python code to create machine learning models including support vector machines, decision tree classifiers, and k-nearest neighbors

  • Evaluate the results of machine learning models for predictive analysis, compare their strengths and weaknesses and identify the optimal model 

Skills you'll gain

Category: Methodology
Category: Github
Category: Jupyter Notebook
Category: Data Science Methodology
Category: K-Means Clustering

Instructors

Rav Ahuja
IBM
39 Courses1,673,968 learners
Alex Aklson
IBM
22 Courses847,570 learners
Aije Egwaikhide
IBM
6 Courses457,204 learners

Offered by

IBM
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