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
In the current digital economy, being able to make informed, data-driven decisions is not an option anymore — it is essential. Simply put, a business that bases its decisions upon data performs better than the rest. Keeping this in mind, the Business Analytics certificate program by Emeritus provides you with the tools and techniques you need to put data to work.
The online program in Business Analytics covers topics like how to collect data, how to set up experiments, and how to learn from data and make decisions. The certification program delves into widely-used frameworks of business analytics: experimentation, biases, prescriptive analytics, descriptive analytics, and predictive analytics. You also learn to implement these frameworks through assignments and case studies.
Moreover, you will join a diverse group of participants from every part of the world through discussion boards where you will share your perspectives and take into account the ones shared by the other participants. After completing the online Business Analytics training course, you also receive a course completion certificate by Emeritus, which can be incorporated in your CV or resume to boost your career opportunities.
The Highlights
- 100 percent online
- Course completion certificate
- Experienced faculty
- Three-month course
- Four to six hours of commitment per week
- Practice assignments
- Industry case studies
- Flexible payment options
Programme Offerings
- online
- Flexible payments
- Expert instructors
- Case Studies
- video lectures
- assignments
- Certificate
- Three months course duration
- In collaboration with Cambridge Judge Business School Executive Education
Courses and Certificate Fees
| Certificate Availability | Certificate Providing Authority |
|---|---|
| yes | Cambridge Judge Business School, Cambridge |
- You will have to pay the requisite course fee of USD 2,000 to enroll in the Business Analytics programme by Emeritus.
- If you cannot pay the entire amount in one go, there is a flexible payment option offered by Emeritus so that you can pay the amount in instalments.
- If you wish to take the course with your colleagues, there is a group discount available.
Business Analytics fee structure
Course | Fees |
Business Analytics | $2,000 |
Discounted fee | $1,487 |
Eligibility Criteria
Certificate Qualifying Details
Candidates will receive the Business Analytics: Decision Making Using Data program certification after completing the entire curriculum of the course.
What you will learn
By the end of the Business Analytics: Decision Making Using Data online training program, you will be able to:
- Identify the role of big data, what it means to you, and what you achieve with it
- Design experiments to glean meaningful data, and make data-driven decisions using it
- Use machine learning models/tools, analyze data to optimize business decisions, and identify neural networks
- Recognize organizational issues when making decisions; identify the ethical and legal issues behind storing, gathering, and using data
- Be able to describe, clean, and collect the data you have, which includes summary statistics
- Recognize different types of biases present in the decision-making process, as well as learn how to ask for the right data
Who it is for
The Business Analytics online course is specifically designed for managers across different industry verticals who are looking to take on analytics-based projects at their organization. Moreover, the program also provides business managers with techniques and tools which will help them transform their organization into a data-driven institution.
Admission Details
Step 1. To become a participant in the online Business Analytics: Decision Making Using Data program by Emeritus, you will first need to visit the course website. Here is the link: https://emeritus.jbs.cam.ac.uk/business-analytics/index.php.
Step 2. After landing on the website, carefully go through course details such as curriculum, duration, and fees.
Step 3. Click on the 'Apply Now button located at the bottom of the page.
Step 4. Register or log in to your Emeritus account using the right credentials.
Step 5. After signing in, you will be prompted to make payment for the course fee. Once you have paid the course fee, you will be enrolled in the course.
The Syllabus
- Benefits of analytics
- Decision traps
- Normal and not-normal distributions
- What is data mining?
- What do you think about the data that you found?
- What kind of data can you find?
- Web scraping
- Application Programming Interface (API)
- Data cleaning
- APIs and Amazon
- Confidence intervals and effect size
- Descriptive statistics
- Introduction to Big Data
- What must Big data mean to you?
- Big Data opportunities
- What is Big Data?
- Challenges for big data
- Four Vs of big data – volume, velocity, variety, and veracity
- Overcoming barriers
- Making experimentation work
- The gold standard
- Decision trees & random forest
- Machine learning vs hypothesis testing
- Support vector machines
- Machine learning algorithms
- Machine learning in practice
- Interpret an analysis
- Hyperparameter optimization
- Machine learning in real world
- Ensemble methods
- Model overfitting
- Supervised machine learning
- The animal neural networks biology
- Choosing network architecture
- Reinforcement learning for businesses
- Applications of neural networks
- Assumptions for neural networks
- How neural networks make predictions
- Recurrent neural networks
- Making a business decision
- What is prescriptive analytics?
- Decision Trees
- Connecting business objectives to predictive analytics
- Deep dive into a particular business model
- smart service Case
- Diversification
- Debiasing and Decision making process
- Risk aversion
- Sunk cost fallacy
- Setting up the right infrastructure
- GDPR
- Making customers comfortable
- Implementation challenges
- Anonymisation and Privacy
- Hacking and insider threats
- Big data strategy