Online Course – Certified Professional Data Internship with Google and IBM by the Institute for Professional Training, IBM

Enhance your career in data science. Acquire foundational skills in data science to prepare for a career or further study in the field.

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קורס אונליין - התמחות מקצועית מוסמכת בנתונים עם Google ו-IBM של המכון להכשרה מקצועית

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

  • Data Science
  • Python Programming
  • Cloud Databases
  • SQL
  • Relational Database Management System (RDBMS)

What you will learn in the course

Courses for which the course is suitable

  • Data Scientist
  • Data Analyst
  • Data key
  • Information Systems Analyst
  • Artificial Intelligence Expert
  • Statistical analyst
  • Software developer with a specialization in data
  • Big Data Expert
  • Business Data Analyst
  • Data Science Project Manager

Internship – 4-part course series

Interested in learning more about data science, but don’t know where to start? This 4-part course series from IBM will provide you with the foundational skills every data scientist needs to prepare you for a career in data science or advanced study in the field.

What will you learn in the internship?

  • What is data science and what are the roles of data scientists.
  • The impact of data science in various fields.
  • How data analysis can help you make data-driven decisions.
  • Getting started in the field without prior knowledge of computer science or programming languages.
  • Understanding concepts such as big data, statistical analysis, and relational databases.
  • Familiarity with open source tools and programs such as Jupyter Notebooks, RStudio, GitHub, and SQL.

Labs and practical projects

You will complete labs and hands-on projects to learn the methodology involved in solving data science problems and apply your new skills and knowledge to real-world datasets.

Certificates and recognition

In addition to your Coursera internship completion license, you will also receive a digital certificate from IBM that recognizes you as an expert in the fundamentals of data science. This training can also be used towards the IBM Data Science Professional Certificate.

Hands-on Learning Project

All courses in the specialization include multiple labs and hands-on exercises to help you gain hands-on experience and skills with a variety of datasets and tools like Jupyter, GitHub, and R Studio. Build your data science portfolio from the materials you produce throughout the program. Projects that conclude the course include:

  • Create and share a Jupyter Notebook containing code blocks and Markdown.
  • Develop a problem that can be solved by applying the data science methodology and explain how to apply each step of the methodology to solve it.
  • Using SQL to query population, crime, and demographic data to identify factors that influence attendance, safety, health, and environmental ratings in schools.

Details of the courses that make up the specialization

What is data science?

Course 1 • 11 hours • 4.7 (72,446 ratings)

Course Details
  • Definition of data science and its importance in today’s data-driven world.
  • Description of the different paths that can lead to a career in data science.
  • A summary of advice given by experienced data science professionals to novice data scientists.
  • Explain why data science is considered the most in-demand job of the 21st century.
Skills you will acquire:
  • Category: Data Science
  • Category: Big Data
  • Category: Machine Learning
  • Category: Deep Learning
  • Category: Data Mining

Course 2 • 18 hours • 4.5 (29,076 ratings)

Course Details
  • Description of the data scientist toolkit including: libraries and items, datasets, machine learning models, and big data tools.
  • Using languages ​​common among data scientists such as Python, R, and SQL.
  • Demonstrate practical knowledge of tools such as Jupyter notebooks and RStudio and enjoy their various features.
  • Create and manage source code for data science using Git and GitHub repositories.
Skills you will acquire:
  • Category: Data Science
  • Category: Python Programming
  • Category: GitHub
  • Category: RStudio
  • Category: Jupyter notebooks

Course 3 • 6 hours • 4.6 (20,348 ratings)

Course Details
  • A description of what data science methodology is and why data scientists need it.
  • Application of the six steps within the CRISP-DM methodology for case study analysis.
  • Evaluation of the appropriate analytical model among predictive, descriptive, and classification models for case study analysis.
  • Determine appropriate data sources for your data analysis methodology.
Skills you will acquire:
  • Category: Data Science
  • Category: Data Analysis
  • Category: CRISP-DM
  • Category: Methodology
  • Category: Data Mining

Course 4 • 20 hours • 4.7 (20,459 ratings)

Course Details
  • Analyzing data within a database using SQL and Python.
  • Creating a relational database and working with multiple tables using DDL commands.
  • Building SQL queries from basic to intermediate level using DML commands.
  • Formulate more powerful queries with advanced SQL techniques like Views, Transactions, Stored Procedures, and Joins.
Skills you will acquire:
  • Category: Python Programming
  • Category: Cloud Databases
  • Category: Relational Database Management System (RDBMS)
  • Category: SQL
  • Category: Jupyter notebooks

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