Get updates on Eligibility, Admission, Placements Fees Structure
Quick Facts
| Medium Of Instructions | Mode Of Learning | Mode Of Delivery |
|---|---|---|
| English | Self Study, Virtual Classroom | Video and Text Based |
Course Overview
A Business Wire report states that 99% of Fortune 1000 firms are investing in data efforts. Big data has revolutionized and continues to revolutionize the global corporate landscape, analysts and data scientists are emerging as valuable assets inside enterprises. The Data Science Essentials online course is designed to teach students the principles of data science as well as the needs of big data analytics.
According to a Research and Markets report, The worldwide worth of the big data analytics industry is expected to be $105 billion by 2027. Working professionals and managers must now grasp the ideas and benefits of data science and utilize it to influence company choices as well as retain and recruit the appropriate personnel to drive transformation. The Data Science Essentials Training teaches the fundamentals of data science for enterprise, helping applicants to identify the value of its technology and use it to achieve success.
The Data Science Essentials syllabus supplements decision-making skills by emphasizing non-technical abilities such as data science project management and execution. This course, led by I School specialists, prepares business executives to grasp the function of data science, its potential relevance for the development of the firm, and how it may be applied in business processes.
The Highlights
- Shareable certificate
- UC Berkeley I School offering
- 6 weeks duration
- Split option of payment
- Projects and assessments
- Self-paced learning
- Course provider Getsmarter
- Online learning
- Downloadable resources
- 8-10 hours per week
Programme Offerings
- Case Studies
- Offline resources
- video lectures
- quizzes
- Self-paced learning
- Infographics
- Live polls
- online learning
Courses and Certificate Fees
| Certificate Availability | Certificate Providing Authority |
|---|---|
| yes | I School Berkeley |
Eligibility Criteria
Certification Qualifying Details
To qualify for the Data Science Essentials certification from UC Berkeley, Entrants must complete the series of learning modules included in the course. Candidates will have to complete the assignments and projects tasks assigned in the program. A sequence of online submitted projects, assignments and classroom activities are monitored to make the report card of students. All the requisites outlined in the coursebook must be met to qualify for the certification.
What you will learn
After completing the Data Science Essentials online course from UC Berkeley I School, Candidates will learn how to make educated decisions about data science and its influence on the organisation, as well as how to build a team capable of providing outcomes through data analytics. Candidates will get a grasp of how complicated data may be used to expand and scale a company, as well as the abilities needed to face the challenges of managing a data science project.
Who it is for
- Non-technical individuals who want to get a deeper understanding of data science and the capacity to make educated judgments about its influence on an organisation.
- Anyone working on data science initiatives and wants to gain a better understanding of how their efforts fit into the larger business environment.
- Managers, data scientists, data analysts who wish to obtain technical expertise to increase a company's data analytics capabilities, and those who run specialised teams will be able to increase awareness through partnerships with other divisions inside the business.
Admission Details
To get admission to the Data Science Essentials online training from UC Berkeley, follow the steps mentioned below:
Step 1. Go to the official course website.
Step 2. Find the ‘Register Now’ button on the course page and click to start the registration
Step 3. Mark the consent box to agree with the provider terms and conditions
Step 4. Create a profile on the Getsmarter by filling in personal details
Step 5. Choose the option sponsor information button to provide details if someone is paying your fee and fill the compulsory billing address
Step 6. Pay the fee and start learning on Getsmarter
The Syllabus
- Review the importance of a shared data science vocabulary
- Recognize key terms that are commonly used in data science
- Describe how becoming data-driven could change an organization
- Explain what an organization requires in order to learn from data
- Discuss the characteristics of a data-driven organization
- Practice using data science software
- Identify how to engage with and navigate data science tools
- Interpret the role of the data science process in business
- Describe the stages of the data science project life cycle
- Investigate how questioning techniques affect the usefulness of the data gathered
- Review the relationship between ethics and data science
- Evaluate how data science can be used to support organizational objectives
- Practice data exploration techniques such as data mining and cleaning
- Identify techniques used by data scientists to mine and clean data
- Discuss how data science techniques and data management can be applied, and how data can empower organizations
- Recognize how data science techniques can be used to address problems in an organization
- Interpret various challenges for data science in organizations
- Identify techniques for gaining insights from data
- Investigate questioning techniques that can help to avoid possible pitfalls during the implementation of data science projects
- Articulate an opinion on employment strategy trends for data science talent
- Discuss why an organization should develop data science skills
- Analyze the issues surrounding retention in data science teams
- Identify relevant data exploration resources
- Investigate ways to ensure that an organization's hiring, retention, and development techniques are optimized for data scientists
- Practice applying data exploration techniques to a given data set
- Discuss the impact on organizations when data science projects are efficiently measured
- Recognize the conditions that facilitate alignment between data science projects and organizational goals
- Determine appropriate metrics for a data science project
- Evaluate the metric used in a data science project and its appropriateness relative to the project and the organization’s greater goals
- Analyze the functions of metrics in an organization's data science projects
- Articulate how organizations conduct the transformation process
- Identify the strategic role of data and analytics produced during historical data science projects
- Analyze the challenges that start-ups face and lessons that larger organizations can learn from them
- Draft a plan for a data science project that facilitates digital transformation in an organization
- Assess the strategies that can be used to initiate digital transformation
I School Berkeley Frequently Asked Questions (FAQ's)
Data Science is the study of obtaining useful insights from massive quantities of data using diverse scientific methodologies, algorithms, and procedures.
According to a Glassdoor report, data science is one of the most demanding and highly paid jobs.
You can complete data science essential certification merely in 6 weeks.
Individuals having good knowledge of data science and algorithms can easily get a job.
Data scientists need various data skills like python, SQL, machine learning, apache-spark, Hadoop, artificial intelligence, data visualisation, etc.