IBM
Applied Data Science Specialization
IBM

Applied Data Science Specialization

Get hands-on skills for a career in data science. Learn Python, analyze and visualize data. Apply your skills to data science and machine learning.

Dr. Pooja
Joseph Santarcangelo
Saishruthi Swaminathan

Instructors: Dr. Pooja

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68,972 already enrolled

Get in-depth knowledge of a subject
4.7

(7,748 reviews)

Beginner level
No prior experience required
Flexible schedule
2 months, 10 hours a week
Learn at your own pace
Build toward a degree
Get in-depth knowledge of a subject
4.7

(7,748 reviews)

Beginner level
No prior experience required
Flexible schedule
2 months, 10 hours a week
Learn at your own pace
Build toward a degree

What you'll learn

  • Develop an understanding of Python fundamentals

  • Gain practical Python skills and apply them to data analysis

  • Communicate data insights effectively through data visualizations

  • Create a project demonstrating your understanding of applied data science techniques and tools

Details to know

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Taught in English

Advance your subject-matter expertise

  • Learn in-demand skills from university and industry experts
  • Master a subject or tool with hands-on projects
  • Develop a deep understanding of key concepts
  • Earn a career certificate from IBM
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Specialization - 5 course series

Python for Data Science, AI & Development

Course 125 hours4.6 (40,166 ratings)

What you'll learn

  • Learn Python - the most popular programming language and for Data Science and Software Development.

  • Apply Python programming logic Variables, Data Structures, Branching, Loops, Functions, Objects & Classes.

  • Demonstrate proficiency in using Python libraries such as Pandas & Numpy, and developing code using Jupyter Notebooks.

  • Access and web scrape data using APIs and Python libraries like Beautiful Soup.

Skills you'll gain

Category: Python Programming
Category: Object Oriented Programming (OOP)
Category: Web Scraping
Category: Data Structures
Category: Pandas (Python Package)
Category: NumPy
Category: Data Collection
Category: Application Programming Interface (API)
Category: Data Import/Export
Category: Jupyter
Category: Computer Programming
Category: Scripting
Category: Data Manipulation
Category: Data Processing
Category: Automation
Category: Programming Principles

Python Project for Data Science

Course 28 hours4.5 (4,525 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: Dashboard
Category: Data Analysis
Category: Data Manipulation
Category: Web Scraping
Category: Python Programming
Category: Data Visualization Software
Category: Data Wrangling
Category: Pandas (Python Package)
Category: Jupyter
Category: NumPy
Category: Data Science
Category: Data Collection
Category: Data Processing

Data Analysis with Python

Course 315 hours4.7 (18,866 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: Regression Analysis
Category: Scikit Learn (Machine Learning Library)
Category: NumPy
Category: Predictive Modeling
Category: Pandas (Python Package)
Category: Data Manipulation
Category: Data Cleansing
Category: Data Pipelines
Category: Exploratory Data Analysis
Category: Data Wrangling
Category: Data Transformation
Category: Data Analysis
Category: Python Programming
Category: Feature Engineering
Category: Predictive Analytics
Category: Statistical Analysis
Category: Data Import/Export
Category: Statistical Modeling
Category: Machine Learning Methods

Data Visualization with Python

Course 420 hours4.5 (11,988 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: Matplotlib
Category: Plotly
Category: Box Plots
Category: Interactive Data Visualization
Category: Seaborn
Category: Scatter Plots
Category: Data Visualization Software
Category: Histogram
Category: Data Visualization
Category: Pandas (Python Package)
Category: Heat Maps
Category: Dashboard
Category: Geospatial Information and Technology
Category: Data Analysis

Applied Data Science Capstone

Course 513 hours4.7 (7,239 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: Exploratory Data Analysis
Category: Data Collection
Category: Plotly
Category: Web Scraping
Category: Predictive Modeling
Category: Data Analysis
Category: Interactive Data Visualization
Category: Data Wrangling
Category: Data Science
Category: Statistical Machine Learning
Category: Data-Driven Decision-Making
Category: Data Presentation
Category: Pandas (Python Package)
Category: Data Storytelling

Instructors

Dr. Pooja
IBM
4 Courses326,081 learners
Joseph Santarcangelo
IBM
33 Courses1,825,740 learners

Offered by

IBM

Build toward a degree

When you complete this Specialization, you may be able to have your learning recognized for credit if you are admitted and enroll in one of the following online degree programs.¹

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Degree credit eligible

This Specialization has ACE® recommendation. It is eligible for college credit at participating U.S. colleges and universities. Note: The decision to accept specific credit recommendations is up to each institution.

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