“Tell me, and I will forget; show me, and I may remember; Involve me, and I will understand.” – Confucius
The need for experiential learning
Communication with learners worldwide has revealed a ubiquitous desire to work on projects that demonstrate their ability to apply a skill or use tools like Python to potential employers.
In addition, educational psychology research shows that application-based projects help students learn how to use their skills in real-world environments.
Guided Projects by Great Learning provide guided instructions to help learners build end-to-end solutions to various business challenges. The projects involve learners applying thought to the problem they solve, a critical component of active learning.
Why are guided projects the preferred learning style?
Learners engage in authentic, real-world tasks in guided projects that feature problem-based instruction. Traditional instruction is topic-based, teaching the concepts before introducing the applications of the concepts covered in the curriculum.
The problem statement in the guided projects, on the other hand, drives the learners to explore possible solutions and think out of the confines of the curriculum to build business solutions.
Recruiters for data science roles at leading companies value hands-on experience more than a theoretical knowledge of data science algorithms. Prospective employees exhibiting expertise in solving a wide range of problems and a diverse portfolio of projects catch the eye of interviewers at all organizations.
When learners have the opportunity to train with hands-on projects, they become more deeply engaged in their career path and have a deeper understanding of a typical project lifecycle.
A 3-week data science journey
Guided projects replicate a typical data science scenario, with a problem statement introducing you to the expected business outcomes and raw unclean data to work on. During the three weeks of the project, learners clean the data, identify the key data points relevant to the problem and present their findings to an industry mentor during weekly live sessions.
The industry mentors are seasoned professionals from the data science domain with extensive experience in leading projects at their organization. Learners engage with the mentors every week during the guided projects, where they receive feedback on what’s working and what areas can be improved.
Guided projects give you hands-on experience and enable you to build a problem-solving mindset with data science tools like Python, SQL, and Tableau. At the end of the project, learners make a presentation for business leaders, explaining their approach to the challenge and the analysis performed on the data.
The guided projects add value to learner portfolios, and learners can apply the invaluable learnings to other data science projects. After all, Data Science is the art of extracting valuable insights from raw data, and Guided Projects aim to teach the best data science practices.
Source: GreatLearning Blog
