Why Data Science?

More and more companies are coming to realize the importance of data science, AI, and machine learning. Regardless of industry or size, organizations that wish to remain competitive in the age of big data need to efficiently develop and implement data science capabilities or risk being left behind.

This Course Is For You If You Want To

• * Learn New Techniques: latest algorithms, cloud solutions, open source tools and data science technologies
• * Improve Your Skills: set you up for success in the digital age
• * Solve real-world problems: by delivering project-based deliverables where you need to apply your knowledge to solve problems

Who Should Take This Course?

• * Newcomers to the field of data science
• * Professionals who need to rapidly upskill and enhance their data science toolkit
• * It is also beneficial to professionals working in a range of business areas, including but not limited to marketing, sales, finance, and operations who want to learn how to use data and programming to increase efficiencies and identify new opportunities for their organization.

Pre-Requisite

• * Newcomers to the field of data science
• * Computer Literacy
• * This course is technical in nature. It is therefore recommended that you have a basic understanding of mathematics and statistics. Basic knowledge of at least one programming language would be beneficial and is recommended but is not required

Our Teaching Philosophy

We believe in the importance of the facilitators’ role, the support of the group and the power of real-time interaction to inspire creative learning

• Our Methodology
• * Live Virtual Class
• * E-Learning (self-paced)
• * Face to face Training
• * Real-Time Chat
• * Live Webinars
• * Case Studies

Curriculum Overview

• This course will provide students with the knowledge, skills and experience to get a job as a Data Scientist -which requires a mix of programming and statistical understanding. The course will teach students to gather data, visualize data, apply statistical analysis to answer questions and make their insights and information as actionable as possible. We cover the fundamentals of the Data Scientist toolkit as well as well as broad set of machine learning algorithms.