Online Course – IBM Certified Professional Certificate in IBM Data Science

Prepare yourself for a career as a data scientist. Develop relevant skills in general and in the field of artificial intelligence in particular, for a sought-after career. Get certified from IBM. No prior experience required.

Suggested by: Coursera (What is Coursera?)

Start your Coursera.com free trial today
קורס אונליין - תעודה מקצועית מוסמכת ב-IBM Data Science של IBM

Professional Certificate

Beginners

No prior knowledge required

Time to complete the course

7-day free trial

No unnecessary risks

Skills you will acquire in the course

  • Databases
  • Data plays
  • Statistical analysis
  • Prediction model
  • Machine learning algorithms
  • Data sampling
  • Python
  • SQL
  • Jupyter notebooks
  • Github
  • Rstudio
  • Pandas
  • Numpy
  • ScikitLearn
  • Matplotlib
  • Financial data processing
  • SQL queries for demographic data
  • Designing graphs and regression models
  • Create a dynamic dashboard
  • Applying predictive algorithms
  • Training and comparing machine learning models

What you will learn in the course

Courses for which the course is suitable

  • Data Scientist
  • Data Analyst
  • Machine learning model developer
  • Data Analyst
  • Data Engineer
  • Artificial Intelligence Expert
  • Data software developer
  • Data Science Project Manager
  • Data Consultant
  • Data scientist

Professional Certificate – 12-lesson course series

Prepare yourself for a career in the fast-growing field of data science . In this program, you can develop the skills, tools, and portfolio that will give you a competitive edge in the job market as an entry-level data scientist in just 5 months. No prior knowledge of computer science or programming languages ​​is required.

Data science involves collecting, cleaning, organizing, and analyzing data to extract useful insights and predict expected outcomes. The demand for skilled data scientists who can use data to tell compelling stories and help decision-makers has never been higher.

You will learn essential skills used by professional data scientists including databases, data visualizations, statistical analysis, predictive modeling, machine learning algorithms, and data sampling. You will also work with the latest languages, tools, and libraries including Python, SQL, Jupyter notebooks, Github, Rstudio, Pandas, Numpy, ScikitLearn, Matplotlib, and more.

Upon completion of the full program, you will build a portfolio of data science projects that will give you the confidence to stand out in job interviews. You will also gain access to the IBM Talent Network, where you can view job postings immediately after they are posted, receive recommendations tailored to your skills and interests, and get tips to set you apart from the rest.

This program is recommended by ACE® and FIBAA — after completing it, you can receive up to 12 academic credits and 6 ECTS points.

Hands-on Learning Project

This professional certificate emphasizes hands-on learning and includes a series of hands-on labs in the IBM cloud that give you practical skills that can be applied to real jobs. You will also have the opportunity to learn how generative AI tools and techniques are used in data science.

Tools you will use: Jupyter / JupyterLab, GitHub, R Studio, and Watson Studio

Libraries you will use: Pandas, NumPy, Matplotlib, Seaborn, Folium, ipython-sql, Scikit-learn, ScipPy, etc.

Projects you will complete:

  • Traversing and Dragging Financial Data with the Pandas Library in Python

  • Using SQL to query demographic data sets of population, crime, and schools

  • Data modeling, graph design, and regression modeling to predict housing prices using Python data science libraries

  • Creating a dynamic dashboard in Python to improve the reliability of domestic flights in the US

  • Applying machine learning algorithms to predict whether a loan case will materialize

  • Training and comparing machine learning models

Details of the courses that make up the specialization

What is data science?

Course 1 • 11 hours • 4.7

  • Define what data science is and why it is important in today’s data-driven world.
  • Describe the different paths that can lead to a career in data science.
  • Summarize the advice given by experienced data science professionals to data scientists starting out.
  • Explain why data science is considered the most in-demand job of the 21st century.

The skills you will acquire

  • Model selection
  • Data Analytics
  • Python programming
  • Data visualization
  • Predictive models

Data science tools

Course 2 • 18 hours • 4.5

  • Describe the data scientist’s arsenal of tools, which includes: libraries and packages, data systems, machine learning models, and Big Data tools.
  • Use common data science languages ​​like Python, R, and SQL.
  • The model has working knowledge of tools like Jupyter Notebooks and RStudio.
  • Create and manage source code for data science using Git and GitHub repositories.

The skills you will acquire

  • Data Science
  • Python programming
  • GitHub
  • RStudio
  • Jupyter Notebooks

Data Science Methodology

Course 3 • 6 hours • 4.6

  • Describe what a data science methodology is and why data scientists need a methodology.
  • Apply the six steps in the Cross-Industry Process for Data Mining (CRISP-DM) to a case study analysis.
  • Evaluate which analytical model is appropriate among predictive, descriptive, and classification models.
  • Determine appropriate data sources for your data science data analysis methodology.

The skills you will acquire

  • Data Science
  • Data Analytics
  • Python programming
  • NumPy
  • Pandas

Python for Data Science, AI, and Development

Course 4 • 25 hours • 4.6

  • Learn Python – the most popular programming language for data science and software development.
  • Apply Python programming principles: variables, data structures, loops, functions, objects, and classes.
  • Model proficiency in using Python libraries such as Pandas and NumPy.
  • Access and manipulate data using APIs and Python libraries like Beautiful Soup.

The skills you will acquire

  • Python programming
  • Dashboards and charts
  • Data visualization
  • Matplotlib

Python for Data Science Project

Course 5 • 8 hours • 4.5

  • Play the role of a data scientist/data analyst working on a real project.
  • Demonstrate your skills in Python.
  • Build a dashboard using Python and libraries such as Pandas, Beautiful Soup, and Plotly.

The skills you will acquire

  • GitHub
  • Jupyter Notebook
  • K-Means Clustering

Databases and SQL for Data Science with Python

Course 6 • 20 hours • 4.7

  • Analyzing data in a database using SQL and Python.
  • Create a relational database and work with multiple tables.
  • Build basic to intermediate level SQL queries.
  • Write more powerful queries using advanced SQL techniques.

The skills you will acquire

  • Python programming
  • Cloud databases
  • SQL

Data analysis with Python

Course 7 • 15 hours • 4.7

  • Developing Python code for cleaning and preparing data for analysis.
  • Perform exploratory data analysis and apply analytical techniques.
  • Build and evaluate regression models using the scikit-learn machine learning library.

The skills you will acquire

  • Machine learning
  • Regression
  • Classification

Data visualization with Python

Course 8 • 20 hours • 4.5

  • Implement data visualization techniques using Python libraries.
  • Create different types of charts.
  • Produce interactive dashboards.

The skills you will acquire

  • Data Science
  • Data Analytics
  • Data generation

Machine Learning with Python

Course 9 • 13 hours • 4.7

  • Describe the different types of machine learning algorithms.
  • Write Python code that implements various classification techniques.
  • Evaluate the results from linear regression.

The skills you will acquire

  • Career development
  • Interview skills

Practical training in data science

Course 10 • 13 hours • 4.7

  • Demonstrate skills in data science modeling and machine learning techniques.
  • Apply your skills to perform data collection, data handling, data analysis, and investigation.

The skills you will acquire

  • Data Science
  • Data Analytics
  • Python programming

Generative AI: Upgrade Your Data Science Career

Course 11 • 12 hours • 4.7

  • Leverage generative AI tools to explore and prepare data.
  • Practice generative AI skills in labs and hands-on projects.

The skills you will acquire

  • Data Science
  • Big Data
  • Machine learning

Data Scientist Career Guide and Interview Preparation

Course 12 • 9 hours • 4.7

  • Describe the role of a data scientist and some career paths.
  • Explain how to build a foundation for a job search.
  • Summarize what a candidate can expect during a typical interview cycle.

The skills you will acquire

  • Data Science
  • Data Analytics
  • CRISP-DM

Related products