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IBM Skills Network Team
Data science professionals are in high demand around the world, and the trend shows no sign of slowing. There are lots of great jobs available, but lots of great candidates too. How can you get the edge in such a competitive field?
Read more
Data science professionals are in high demand around the world, and the trend shows no sign of slowing. There are lots of great jobs available, but lots of great candidates too. How can you get the edge in such a competitive field?
Read more
Data science professionals are in high demand around the world, and the trend shows no sign of slowing. There are lots of great jobs available, but lots of great candidates too. How can you get the edge in such a competitive field?
This course will prepare you to enter the job market as a great candidate for a data scientist position. It provides practical techniques for creating essential job-seeking materials such as a resume and a portfolio, as well as auxiliary tools like a cover letter and an elevator pitch. You will learn how to find and assess prospective job positions, apply to them, and lay the groundwork for interviewing.
The course doesn’t stop there, however. You will also get inside tips and steps you can use to perform professionally and effectively at interviews. You will learn how to approach a code challenge and get to practice completing them. Additionally, it provides guidance about the regular functions and tasks of data scientists, as well as the opportunities of the profession and some options for career development.
Let seasoned professionals share their experience to help you get ahead and land the job you want!
Register for this course and see more details by visiting:
OpenCourser.com/course/mb0rbw/data
What's inside
Syllabus
Building a Foundation
Your job search will be much more effective if you do some primary work before you begin. In Building a Foundation, you’ll learn how to clearly understand the jobs you will be looking for. You’ll learn how to write a basic resume and collect your previous work examples into a portfolio. You’ll also create some other materials that will be useful, such as a cover letter and an elevator pitch
Read more
Syllabus
Building a Foundation
Your job search will be much more effective if you do some primary work before you begin. In Building a Foundation, you’ll learn how to clearly understand the jobs you will be looking for. You’ll learn how to write a basic resume and collect your previous work examples into a portfolio. You’ll also create some other materials that will be useful, such as a cover letter and an elevator pitch
Read more
Applying and Preparing to Interview
Job Seeking and Interview Preparation helps you understand how to put yourself forth as a memorable candidate. You’ll get guidance on researching prospective companies and assessing job leads to sift out the ones you want to focus on. You’ll learn about rehearsing for interviews and why it can make a big difference in your performance. And you’ll learn ways to network and let people you meet help you find your ideal role.
Interviewing
After you’ve attracted a company’s attention, it’s important to know how to follow through. The Interviewing module will guide you through the interview process from beginning to end. You’ll learn about common types of interviews and what to expect from them, including code challenges. You’ll also learn some crucial tips for making a great impression in a final interview and how to follow up so that you stand out from the crowd.
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Develops interview skills, which are highly relevant in industry
Taught by IBM Skills Network Team, who are recognized for their work in data science
Develops professional skills in data science, which are highly relevant in industry
Provides guidance for building a resume and portfolio, which are essential in job seeking
Develops professional communication skills, such as elevator pitches and cover letters
Examines job searching, which is highly relevant to data science
Save this course
Save Data Scientist Career Guide and Interview Preparation to your list so you can find it easily later:
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Activities
Be better prepared
before
your course. Deepen your understanding
during
and
after
it. Supplement your coursework and achieve mastery of the topics covered
in Data Scientist Career Guide and Interview Preparation with these
activities:
Read 'Introduction to Data Science' by Jake VanderPlas
Show steps
This book provides a comprehensive overview of data science concepts and techniques, which will enhance your understanding of the field.
View
Python Data Science Handbook: Essential Tools...
on Amazon
Show steps
-
Read each chapter thoroughly.
-
Take notes on key concepts and examples.
-
Complete the exercises at the end of each chapter.
Complete code challenges on platforms like HackerRank and LeetCode
Show steps
Practicing code challenges sharpens your problem-solving skills and prepares you for technical interviews.
Browse courses on
Coding Challenges
Show steps
-
Choose a platform and start solving problems.
-
Start with easier problems and gradually increase the difficulty.
-
Review your solutions and identify areas for improvement.
Join a data science study group or online community
Show steps
Engaging with peers can provide valuable insights, support, and motivation throughout your job search journey.
Show steps
-
Search for study groups or online communities focused on data science.
-
Join the group and actively participate in discussions and activities.
-
Share your knowledge and experiences with others.
Four other activities
Expand to see all activities and additional details
Show all seven activities
Build a simple data visualization portfolio
Show steps
Creating a portfolio of your data visualizations will showcase your skills and help you stand out to potential employers.
Browse courses on
Data Visualization
Show steps
-
Gather data on a topic that interests you.
-
Clean and prepare the data.
-
Choose appropriate visualization techniques to present the data.
-
Create interactive or static visualizations using tools like Tableau or Python.
Reach out to professionals in the data science field
Show steps
Finding a mentor can provide you with valuable guidance, support, and insights throughout your career journey.
Show steps
-
Identify potential mentors who work in the data science field.
-
Reach out to them via email or LinkedIn.
-
Schedule a meeting to discuss your career goals and seek their advice.
Attend industry events and conferences
Show steps
Attending industry events allows you to connect with professionals in the data science field, explore job opportunities, and stay updated on the latest trends.
Show steps
-
Research upcoming industry events and conferences related to data science.
-
Register and attend the events.
-
Network with attendees, including recruiters and hiring managers.
Develop a personal data science project
Show steps
Working on a personal project allows you to apply your data science skills, explore your interests, and build a portfolio of your work.
Browse courses on
Data Science Projects
Show steps
-
Identify a problem or topic that interests you.
-
Gather and prepare the necessary data.
-
Develop a model or solution to address the problem.
-
Evaluate the results of your project.
Read 'Introduction to Data Science' by Jake VanderPlas
Show steps
This book provides a comprehensive overview of data science concepts and techniques, which will enhance your understanding of the field.
View
Python Data Science Handbook: Essential Tools...
on Amazon
Show steps
Show steps
Show steps
- Read each chapter thoroughly.
- Take notes on key concepts and examples.
- Complete the exercises at the end of each chapter.
Complete code challenges on platforms like HackerRank and LeetCode
Show steps
Practicing code challenges sharpens your problem-solving skills and prepares you for technical interviews.
Browse courses on
Coding Challenges
Show steps
Show steps
Show steps
- Choose a platform and start solving problems.
- Start with easier problems and gradually increase the difficulty.
- Review your solutions and identify areas for improvement.
Join a data science study group or online community
Show steps
Engaging with peers can provide valuable insights, support, and motivation throughout your job search journey.
Show steps
Show steps
Show steps
- Search for study groups or online communities focused on data science.
- Join the group and actively participate in discussions and activities.
- Share your knowledge and experiences with others.
Four other activities
Expand to see all activities and additional details
Show all seven activities
Build a simple data visualization portfolio
Show steps
Creating a portfolio of your data visualizations will showcase your skills and help you stand out to potential employers.
Browse courses on
Data Visualization
Show steps
Show steps
Show steps
- Gather data on a topic that interests you.
- Clean and prepare the data.
- Choose appropriate visualization techniques to present the data.
- Create interactive or static visualizations using tools like Tableau or Python.
Reach out to professionals in the data science field
Show steps
Finding a mentor can provide you with valuable guidance, support, and insights throughout your career journey.
Show steps
Show steps
Show steps
- Identify potential mentors who work in the data science field.
- Reach out to them via email or LinkedIn.
- Schedule a meeting to discuss your career goals and seek their advice.
Attend industry events and conferences
Show steps
Attending industry events allows you to connect with professionals in the data science field, explore job opportunities, and stay updated on the latest trends.
Show steps
Show steps
Show steps
- Research upcoming industry events and conferences related to data science.
- Register and attend the events.
- Network with attendees, including recruiters and hiring managers.
Develop a personal data science project
Show steps
Working on a personal project allows you to apply your data science skills, explore your interests, and build a portfolio of your work.
Browse courses on
Data Science Projects
Show steps
Show steps
Show steps
- Identify a problem or topic that interests you.
- Gather and prepare the necessary data.
- Develop a model or solution to address the problem.
- Evaluate the results of your project.
Career center
Learners who complete Data Scientist Career Guide and Interview Preparation will develop knowledge and skills
that may be useful to these careers:
Data Scientist
Data Scientist
A Data Scientist is a professional that uses their knowledge of data and statistics to solve business problems. They are responsible for collecting, cleaning, and analyzing data, as well as developing and deploying machine learning models. The Data Scientist Career Guide and Interview Preparation course can help you develop the skills you need to become a successful Data Scientist. The course will teach you how to find and assess prospective job positions, apply to them, and lay the groundwork for interviewing.
Machine Learning Engineer
Machine Learning Engineer
A Machine Learning Engineer is a professional that designs and builds machine learning models. They work closely with Data Scientists to develop and deploy models that solve business problems. The Data Scientist Career Guide and Interview Preparation course can help you develop the skills you need to become a successful Machine Learning Engineer. The course will teach you how to find and assess prospective job positions, apply to them, and lay the groundwork for interviewing.
Data Analyst
Data Analyst
A Data Analyst is a professional that analyzes data to identify trends and patterns. They work with businesses to help them make better decisions. The Data Scientist Career Guide and Interview Preparation course can help you develop the skills you need to become a successful Data Analyst. The course will teach you how to find and assess prospective job positions, apply to them, and lay the groundwork for interviewing.
Statistician
Statistician
A Statistician is a professional that uses mathematical and statistical models to analyze data. They work with businesses and governments to help them make informed decisions. The Data Scientist Career Guide and Interview Preparation course may be useful for Statisticians who want to develop their data analysis skills.
Data Architect
Data Architect
A Data Architect is a professional that designs and manages data systems. They work with businesses to help them make the most of their data. The Data Scientist Career Guide and Interview Preparation course may be useful for Data Architects who want to develop their data analysis skills.
Software Engineer
Software Engineer
A Software Engineer is a professional that designs, develops, and maintains software systems. They work with businesses to help them solve business problems. The Data Scientist Career Guide and Interview Preparation course may be useful for Software Engineers who want to develop their data analysis skills.
Financial Analyst
Financial Analyst
A Financial Analyst is a professional that analyzes financial data to make investment recommendations. They work with businesses and individuals to help them make informed investment decisions. The Data Scientist Career Guide and Interview Preparation course may be useful for Financial Analysts who want to develop their data analysis skills.
Marketing Analyst
Marketing Analyst
A Marketing Analyst is a professional that analyzes marketing data to identify trends and patterns. They work with businesses to help them improve their marketing campaigns. The Data Scientist Career Guide and Interview Preparation course may be useful for Marketing Analysts who want to develop their data analysis skills.
Product Manager
Product Manager
A Product Manager is a professional that is responsible for the development and marketing of a product. They work with engineers, designers, and marketers to bring a product to market. The Data Scientist Career Guide and Interview Preparation course may be useful for Product Managers who want to develop their data analysis skills.
Data Engineer
Data Engineer
A Data Engineer is a professional that builds and maintains data pipelines. They work with businesses to help them get the data they need to make informed decisions. The Data Scientist Career Guide and Interview Preparation course may be useful for Data Engineers who want to develop their data analysis skills.
Chief Data Officer
Chief Data Officer
A Chief Data Officer is a senior executive who is responsible for the development and implementation of data strategies. They work with businesses to help them make the most of their data. The Data Scientist Career Guide and Interview Preparation course may be useful for Chief Data Officers who want to develop their data analysis skills.
Project Manager
Project Manager
A Project Manager is a professional that is responsible for the planning and execution of a project. They work with stakeholders to ensure that the project is completed on time, within budget, and to the required quality. The Data Scientist Career Guide and Interview Preparation course may be useful for Project Managers who want to develop their data analysis skills.
Data Strategist
Data Strategist
A Data Strategist is a professional that helps businesses develop and implement data strategies. They work with businesses to help them make the most of their data. The Data Scientist Career Guide and Interview Preparation course may be useful for Data Strategists who want to develop their data analysis skills.
Business Analyst
Business Analyst
A Business Analyst is a professional that analyzes business processes to identify areas for improvement. They work with businesses to help them improve their efficiency and profitability. The Data Scientist Career Guide and Interview Preparation course may be useful for Business Analysts who want to develop their data analysis skills.
Operations Research Analyst
Operations Research Analyst
An Operations Research Analyst is a professional that uses mathematical and statistical models to solve business problems. They work with businesses to help them improve their efficiency and profitability. The Data Scientist Career Guide and Interview Preparation course may be useful for Operations Research Analysts who want to develop their data analysis skills.
For more career information including salaries, visit:
OpenCourser.com/course/mb0rbw/data
Reading list
We've selected 14 books
that we think will supplement your
learning. Use these to
develop background knowledge, enrich your coursework, and gain a
deeper understanding of the topics covered in
Data Scientist Career Guide and Interview Preparation.
Provides a comprehensive overview of data science, including the fundamental concepts, techniques, and tools used in the field. It valuable resource for anyone who wants to learn more about data science and its applications in business.
Provides a comprehensive introduction to machine learning, with a focus on the practical aspects of data science. It covers a wide range of topics, including supervised learning, unsupervised learning, and deep learning.
Provides a hands-on introduction to data science, using Python. It covers a wide range of topics, including data cleaning, data exploration, and machine learning.
Provides a comprehensive introduction to Python for data analysis. It covers a wide range of topics, including data cleaning, data exploration, and data visualization.
Save
Provides a comprehensive introduction to R for data science. It covers a wide range of topics, including data cleaning, data exploration, and data visualization.
Provides a comprehensive introduction to deep learning for natural language processing. It covers a wide range of topics, including word embeddings, recurrent neural networks, and attention mechanisms.
Provides a comprehensive introduction to TensorFlow, a popular open-source deep learning library. It covers a wide range of topics, including neural networks, convolutional neural networks, and recurrent neural networks.
Provides a comprehensive introduction to PyTorch, a popular open-source deep learning library. It covers a wide range of topics, including neural networks, convolutional neural networks, and recurrent neural networks.
Provides a comprehensive introduction to natural language processing, using Python. It covers a wide range of topics, including text preprocessing, text classification, and text generation.
Save
Provides a comprehensive introduction to computer vision. It covers a wide range of topics, including image processing, image segmentation, and object recognition.
Provides a comprehensive introduction to pattern recognition and machine learning. It covers a wide range of topics, including supervised learning, unsupervised learning, and reinforcement learning.
Provides a comprehensive introduction to information theory, inference, and learning algorithms. It covers a wide range of topics, including probability theory, Bayesian inference, and reinforcement learning.
Provides a comprehensive introduction to reinforcement learning. It covers a wide range of topics, including Markov decision processes, value functions, and policy gradient methods.
Provides a comprehensive introduction to deep reinforcement learning. It covers a wide range of topics, including deep neural networks, deep Q-learning, and policy gradient methods.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/mb0rbw/data
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Introduction to Software Engineering
Effort
3 weeks of study, 1-2 hours/week
Level
Introductory
Via
Coursera
Institution
IBM
Instructor
IBM Skills Network Team
Language
English
Transcripts
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Good to know
Develops interview skills, which are highly relevant in industry
Taught by IBM Skills Network Team, who are recognized for their work in data science
Develops professional skills in data science, which are highly relevant in industry
Provides guidance for building a resume and portfolio, which are essential in job seeking
Develops professional communication skills, such as elevator pitches and cover letters
Examines job searching, which is highly relevant to data science
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