Data Science Bootcamp: Data Science Certification Courses

Data is at the heart of nearly every aspect of our modern lives. From smartphones and social media to mobile banking and cybersecurity, our world is growing increasingly digital – and that means an increased reliance on data, data integrity, and data science. The job market has responded in kind – according to the Bureau of Labor Statistics, data science is one of the nation’s fastest-growing occupations, with an anticipated growth rate of 31% through 2029.

However, the data landscape is evolving. The workforce needs more people who can work responsibly with data, leverage the power of artificial intelligence, and build visualizations that are accessible to everyone to help the business achieve its goals. Technological advancements are moving quickly, and, quite simply, there are not nearly enough people equipped with the skills needed to fill the open data professional positions.

With XCEED Data Science Bootcamp, you can become the type of professional that organizations need to make smarter, data-driven business decisions. This data science bootcamp program is designed to take you from little or no experience to a ready-to-hire data professional by providing you with the most up-to-date skills and hands-on experience that companies look for.

Take advantage of a market-driven curriculum, enrol in the data science certification course  that’s designed to close the skills gap and gain an edge in a competitive, rapidly-growing job market.

Industry Certifications

• Data Analyst Associate
• IBM Data Analyst Professional Certificate
• IBM Data Science Professional Certificate

In the 460-hour Data Science and Analytics Bootcamp, you will attend lectures, take part in individual and group exercises, and gain access to virtual labs and real-world projects that teach you how to use data to gain business insight while using data analytics and data science best practices. You will complete three experiential training projects in the data science bootcamp that you can showcase on your personal portfolio when applying to jobs in the field. Classes are taught by instructors who are leaders in the industry and who bring a wealth of knowledge and experience to the learning environment. You will benefit from your instructors’ current industry expertise as well as from their unique insider’s understanding of the fast-paced field of data science and analytics.

The Program structure:

• Introduction Course
• Professional Bootcamp
• Data Driven Story Telling
• Data Wrangling and Analytics
• Data Science and Business Intelligence
• Capstone Project

This Program is Perfect For

The accelerated Data Science Bootcamp is built for learners of any professional background who have a strong affinity for technical solutions, enjoy aspects of conceptual and visual design, and seek creative ways to solve problems.

The goal of the data science bootcamp is to take you from little or no experience to a ready-to-hire data professional by providing you with the most up-to-date skills and hands-on experience that companies look for in candidates. Data professionals who opt for data science certification courses  have many advantages over other job seekers because they can organize business requirements into data requirements, see the big picture, and work on a variety of data ingestion, cleaning, and analysis assignments.

Learning Outcomes:

By the end of the Data Science & Analytics Bootcamp program the student will be able to:

• Import data into databases, query data, join data together, filter and sort data, create views, and
• export data using SQL.
• Understand how statistics and probability are used in business decision making.
• Communicate data insights to stakeholders using story points that speak to their audience’s needs
• and expectations.
• Apply core programming concepts such as expressions, data types, variables, functions, loops,
• and arrays.
• Use industry-standard software to automate data wrangling processes including sourcing,
• curating, and importing data, exploratory data analysis, data cleansing, and data visualization.
• Produce effective data visualizations that show the most important parts of data to stakeholders
• in a clear and simplified way.
• Use SQL programming to code stored procedures, triggers, cursors, and query optimization.
• Develop ETL scripts and data pipelines combining the use of SQL and Python.
• Develop and apply best practices for reporting, graphs and charts, and dashboards in a way that
• can be applied in any business intelligence application.
• Understand core concepts and methods used for big data and IoT, including characteristics of big
• data, data warehousing, data lakes, data virtualization, and cloud-based data infrastructure
• services.
• Investigate and apply supervised and unsupervised machine learning algorithms, including
• classification, clustering, association rules, and time-series forecasting