Basic to Intermediate Course in Statistics for Data Scientists
R10 000
About this course
Countdown till this short course launches!
Why Data Scientists need Statistical Skills?
More than ever before, organisations today are having to analyse vast amounts of data and are grappling with how they can make sense of the information hidden in the data to solve vexing problems in the world of business and government. For example, a business manager may want to know the characteristics of customers who are likely to buy the business’ products so that scarce resources can be targeted to this customer segment to maximize conversion rates and ultimately profits.
The data scientist uses statistical models, among other tools, to extract information from the data and generate actionable insights that can solve problems and achieve the organisation’s objectives.
Data scientists know that statistics is a powerful tool in the process of solving problems and making sound business decisions.
Using statistical methodologies and techniques such as data exploration, detailed analysis and modelling, the data scientist will gain a deeper understanding in to the structure of the data and provide management with high-level information to identify opportunities for business growth and solve problems.
To make sense of it all, a thorough understanding of the wonderful world of statistics is paramount.
Now you can see why this profession is in high demand!
Basic to Intermediary Course in Statistics for Data Scientists |
Course FeaturesR 10 000 |
|---|---|
|
Launch |
March 2021 |
|
Period of Course |
15 weeks |
|
Day |
Every Saturday (except long weekends or holiday periods) from 09h00 to 13h00 |
|
Contact time |
4 hours (9h00 – 13h00) |
|
Hand-on Teaching by Expert Tutor (35 years of experience) |
|
|
Notes handed out during class. |
|
|
Extra lessons available |
|
|
Certificate to be issued to successful candidates. |
|
| Enquire Now |
Frequently Asked Questions
How much is this course?
R 10 000 per attendee in full or in 2 instalments
What are examples of careers for data scientists?
Common careers in Data Science:
- Data Scientist
- Data Analyst
- Business Intelligence Specialist
- Data Architect
- Business Analyst
- Business Information Technologist
What background knowledge do I need for this program?
This short course is open for anyone with any job and academic background.
Does the course material cover any computer science work?
The course does not include Computer Science, Machine Learning and Programming. Note, however, that Machine Learning is based on a Statistical and Mathematical Framework which is covered in the course.
What assignments need to be completed for this course?
- Weekly assignments to be completed by attendees.
- The assignments to count 30%, CAM.
- Class Assignments are done in class.
Are extra lessons available for students?
Extra lessons, individual assistance to students attending regularly (minimum 80% of all lessons). Extra lessons to be held on Saturdays from 2 pm to 4 pm for students by appointment.
When is the final exam?
Final examination in week 16, three (3) hours (weight = 70%).
Syllabus
Topic 1 0/1
Introduction and concepts
1 hour
Topic 2 0/4
Essential skills in Data science
1 hour
Topic 3 0/10
Statistical concepts in the exploration of data sets
12 hours
Topic 4 0/11
Basic probability concepts / Bayesian Theorem/decision trees
8 hours
Topic 5 0/4
Probability distributions
6 hours
Topic 6 0/4
Confidence intervals
4 hours
Topic 7 0/2
Hypothesis testing
6 hours
Topic 8 0/6
Hypothesis tests/cross tabulations
6 hours
Topic 9 0/1
Analysis of Variance (ANOVA)
4 hours
Topic 10 0/3
Statistical models
6 hours
Topic 11
Introduction to Linear Algebra/Linear Equations
6 hours
Reviews
Our course begins with the first step for generating great user experiences: understanding what people do, think, say, and feel. In this module, you’ll learn how to keep an open mind while learning.