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Quick Facts

Medium Of Instructions	Mode Of Learning	Mode Of Delivery
English	Self Study, Virtual Classroom	Video and Text Based

Course Overview

Aspirants learn to develop communication skills in a data-driven culture by taking up the Data Science (Online) programme. It is an executive programme extended by Haas Berkeley’s Executive Education (ExecEd). Learners will use mathematical and statistical concepts to analyze and interpret data and analyze data using Jupyter Notebook – an interactive open-source platform used for computational analysis.

A weekly ‘prep session’ is arranged to introduce the preceding module for candidates’ understanding. Over ten weeks of Haas UC Berkeley ExecEd's Data Science Online course, students will be exposed to data manipulation techniques, with various company examples and industry case studies, spread across the eight learning modules.

A verified certificate by Haas UC Berkeley also becomes available once candidates fulfill the qualification criteria. Moreover, the Data Science Online certification course is led by some of the top industry experts on digital transformation through live webinars and sessions, along with academic experts.

Throughout the online programme, students can engage in peer discussions under the supervision of the program facilitators and access different quizzes and assignments to revise the topics learned in the course.

The Highlights

Executive programme in Data Science
Haas UC Berkeley verified certification course
Real-world examples
Case studies
Company examples
Live sessions
Live webinars and interviews with industry experts
Weekly prep sessions
Experienced instructors
E-Learning
Two-week learning labs
Career-focused learning
10-week programme

Programme Offerings

advanced-level course
Company examples
Case Studies
Career-focused learning
Live webinars and interviews
Technical workshops
Recognised certificate
Online-scheduled classes
Learning labs
Moderated discussions

Courses and Certificate Fees

Certificate Availability	Certificate Providing Authority
yes	Haas School of Business, Berkeley

Enrolling in this program will cost you $2,850.
A special discount of 20% will be available to candidates who join through a group pricing modal.
Candidates can also avail of a $285 discount if they join via referrals.
Flexible payment options are available in three installments.

Data Science (Online) course fee structure

Course Name	Fee in USD
Data Science (Online)	$2,850

Eligibility Criteria

Candidates interested in joining the Data Science (Online) course should possess an aptitude for quantitative concepts to excel. However, there are no formal prerequisites as such.

To receive a recognized certificate from Haas UC Berkeley Executive Education, candidates must secure at least 80% to obtain a certificate of completion and pass the programme. However, learners of the Data Science (Online) programme by UC Berkeley ExecEd are generally graded as pass or fail; they do not receive a specific grade.

What you will learn

Mathematical skillStatistical skillsMachine learningData science knowledge

After completing the Data Science (Online) course by Berkeley, learners will have expertise in:

Data terminologies
Techniques of data to gain business insights
Methods to derive answers for business questions
Data presentation
Data interpretation using standard techniques
Data strategy and decision-making

Who it is for

The Data Science (Online) programme by Berkeley will be interesting for those employed in the technology-driven industries. Individuals who can benefit include:

R&D managers
Technology consultants
Data science managers
Business strategists
Performing marketing professionals
Product engineers
Human resource professionals
Product managers

Admission Details

Candidates who want to pursue the Haas UC Berkeley ExecEd's Data Science (Online) programme can continue learning the course after taking a free preview of the programme. They can avail the preview by following the steps mentioned below:

Step 1. Head to the official course page here – https://em-executive.berkeley.edu/data-science and read through the offerings of the course.

Step 2. Then, locate and click on the ‘Preview this Programme for Free’ tab at the bottom of the course webpage.

Step 3. A dialogue box will pop up. Enter required data fields such as name, phone number, email address, any work experience, and country.

Step 4. A coupon and brochure will be mailed to your registered email ID, which you can use to avail a discount if you decide to continue the programme.

Application Details

Candidates interested in Haas UC Berkeley ExecEd's Data Science (Online) certification programme need not fill or print applications for enrolment. Details entered to obtain the preview of the programme will suffice for enrolment.

The Syllabus

Compare categorical vs. numerical data.
Explore the basic ways that data reveal information.
Learn from a healthcare example: HMO membership and doctor visits using aggregated data.
Become acquainted with Jupyter Notebook, Python, and Panda.

Learn to define types of data samples, sampling variation, and quality.
Identify and define foundational sampling concepts.
Identify and mitigate bias when sampling data.
Evaluate examples that illustrate joint, marginal, and conditional probability: Comcast, Google, and Nextag.

Identify the basic tenets of experimentation.
Identify and discriminate between one-sided and two-sided statistical tests.
Complete problem sets using the 4M model (Motivation, Method, Mechanics, and Message).
Analyze an industry example: 24 Hour Fitness tests a new proprietary diet—testing between control and treatment groups.

Identify conditions for using and interpreting linear and curved patterns.
Examine curved (non-linear) patterns as applied to vehicle weight and fuel efficiency.
Complete problem sets using the 4M model for credit cards, crime, and housing prices in Philadelphia.

Define and apply the simple regression model and identify conditions for its use.
Apply and interpret prediction intervals.
Identify three major problems that affect regression models: changing variation in data, outliers, and dependence among observations.
Practice with a retail example: use regression modeling to determine the location of a franchise outlet.

Discriminate between marginal and partial slopes.
Articulate inference in the multiple regression model.
Summarize the process of fitting and building a multiple regression model.
Learn from a financial example: build a multiple regression model to explain the returns on Sony’s stock.
Practice with a human resources example: analyze salary data using MRM to identify gender imbalances.

Discriminate between supervised, semi-supervised, and unsupervised learning.
Examine machine learning approaches, including the “bag-of-words” method for supervised learning.
Practice forecasting by using time series regressions.
Explore a cybersecurity example: machine learning for spam detection.

Review the requirements for building effective data science teams.
Continue the exploration of building a data-driven culture.
Evaluate an advertising example: Rocket Fuel’s conversion rate, benefit, ROI, opportunity cost, and A/B testing.

Instructors

Haas School of Business, Berkeley Frequently Asked Questions (FAQ's)

1: Which companies’ profiles are included in examples?

Berkeley’s Data Science (Online) programme has a strong industrial interface, especially with Silicon Valley. Some of the companies studied are Amazon, Uber, eBay, Gallup, and StubHub.

2: What industries are studied in the course?

The Data Science (Online) course by Berkeley analyses the economy where data is used. Industries such as FinTech/Financial Services, Healthcare, Information Technology, Manufacturing, and Retail are studied.

3: What type of cases are included in the programme?

The categories of case studies included in this course are Maersk for supply chains, Deutsche Bank for financial, Rippleworks, and the healthcare industry for social impacts.

4: Can I avail of any financial discounts?

Group applications call in a discount of 20% from the fee at a special enrolment price. By referring more executives to the Data Science (Online) programme by Berkeley, you also get an additional discount of $285 from the total fee.

5: How much time on an average should I spend per week to complete the course?

You can complete the Data Science (Online) course by Berkeley in 10 weeks by studying at least 6-8 hours per week.