1-Day Introduction to Data Science(LIVE Stream)
Your Step-By-Step Guide in Starting Your Data Science Journey
Demand for Data Scientists has Increased 663% in Five Years, and the Call for Machine Learning Skills is Up to 809%
Get the skills today’s employers demand. Many companies today are seeking talents with the capabilities to transform data sets into strategic forecasts, predictive models, customer segmentation and recommendation engines. Begin your journey into Data Science! Even if you’ve never written a line of code in your life, you’ll be able to follow this course and understand how you can use apply Data Science skills to any business and industry.
Learn the Critical Elements of Data Science, from Visualization to Databases, Python and More
In this 1-day course equipped you with foundational Data Science skills and prepares you for more advanced data Science topics in future. Topics cover will include introduction to data science, consisting of data management, data visualization, data preparation, data analysis, data science modeling, and techniques to decision making with data. The students can expect to learn basic knowledge of data science and how it can be applied to the real life.
- What is Data Science exactly?
- Who are the key stakeholders involved?
- Where does data come from?
- What is the difference between Python and R Programming?
- Understanding the Concepts of Machine Learning and Algorithms
- How can I apply Data Science for Data Analysis and Data Modelling results
- How to tell a story about your data, which is one of the most important lessons.
Who Should Attend?
- Individuals with an interest or need to understand and design data science
- Adult learners with some computer knowledge and a keen interest in data
Jackie is an innovative leader, he contributes great and strategic ideas to the current market. I had the pleasure of working with Jackie in creating a user-centric mobile application. As far as it goes, Jackie would be an asset to any team. Mark Ong, Senior UX Designer at Clearisk
Jackie is an active thought leader who voices his insights and experience. He is an academic genius who has conquered the book of knowledge and an innovator who will define new categories. – Poon Da Qian, CEO, BUTLER
I received timely and insightful feedback from him as needed and learnt the crucial steps to take note when dealing with datasets. He has been a friendly, helpful and knowledgeable mentor along the way and I highly recommend those who need a kickstart in data science/analytics to get his projects he offers to mentor you. Nicholas Tan
Data Scientist: Mr Jackie Tan (Co-Founder of UpLevel & FundMyLife. Forbes 30 Under 30)
Jackie is the co-founder of UpLevel, a data science startup that helps companies co-design projects to solve data problems, discover data science talents and train these talents. Jackie is also the co-founder of fundMyLife, a financial planning online platform that uses an algorithm to connect users with financial advisors based on the questions they ask. Named Forbes 30 under 30 for his work in fintech, Jackie is also known as a leader in fintech in South East Asia.
Jackie has personally trained and coached over 300 professionals in the area of data science, Python programming and coding. Jackie holds a Bachelor of Science (Honours) and is currently pursuing his PhD with Nanyang Technological University. Jackie has also mentored 4 groups of startup to achieve milestones for Startup SG Founder grants of over $100,000 funding.
Jackie has written extensively on entrepreneurship on startup publications such as e27 and Tech in Asia, and has spoken on innovation, data science, and entrepreneurship on platforms such as TEDx, SGInnovate, and Deep Learning in Finance.
- Introduction to Data Science
- What is and isn’t data science
- The data science process
- What does it mean to do data science in an organization
- How to tell whether your organization is ready for data science
- Toolkits and skillsets of a data scientist
- Types of data science work in an organization
- Sources of data for data science
- Practical data storytelling techniques
- Where to go from here?
- Useful resources and guides