Certification Course in Data Science

Overview

In our ever data-centric world, introducing high school students to data science early on
is crucial. As technology expands access to complex datasets, the demand for skilled
data scientists rises. Today’s high schoolers, immersed in a tech-savvy global
environment, possess a unique ability to absorb and apply data.
Early exposure not only builds a solid foundation but also enhances their adaptability to
evolving technologies. While not all may pursue a career as Data Scientists, this
functional knowledge provides a competitive edge in the job market, enriching their skill
set and adaptability.

Why Choose this Program?

1. Develop advanced knowledge in data analytics, mastering statistical techniques, and gaining expertise in acquiring, querying, and analyzing diverse datasets.
2. Cultivate critical thinking skills to make informed inferences, ensuring a solid
   foundation in statistical machine learning and artificial intelligence for data
   analysis.
3. Hone transferable skills in research, report writing, presentations, and IT,
   enhancing practical experience in typical data analytics workflows for real-world
   application.
4. Achieve a well-rounded proficiency in classical and modern data analytics
   techniques, setting the stage for a successful career in Data Science.

Salient Features of This Program

1. Interactive Learning through Hybrid Approach
2. Application-Oriented Case Studies
3. Engagement through Class Participation
4. Diverse Learning Resources
5. Experiential Learning through Presentations and Guest Speakers

You Get A Completion Certificate

Upon completion of the Data Science Certification Course, you will be awarded a
certificate acknowledging your proficiency in the field of Data Science. This
accomplishment serves as a validation of your skills, enhancing your career prospects
by unlocking superior opportunities. The certificate underscores your mastery in Data
Science, positioning you as a sought-after professional in the field.

Course Curriculum

• Intro to Python
  • Introduction to the most user-friendly language, Python! Learn types of Data, Multidimensional lists, Functions, and  Dictionaries.

• Python Fundamentals
  • Understanding Global and Local Variables, init function, Packages and modules with PIP, and Exceptional handling.

• Data Handling using Python
  • Introduction to libraries – Numpy, Pandas, Matplot and Seaborn.

• Data Analysis
  • Understanding Analysis of Data using Numpy, Pandas, Matplot, and Seaborn Libraries.

• Intro to Machine Learning
  • Introduction to Machine Learning and types. Understanding training and testing data, Pickling and Scaling, Classification and Regression introduction.

• Supervised Learning Algorithm
  • Understanding Linear and Logistic Regression; Understanding Supervised Learning Algorithms-Support Vector Machine.
• Unsupervised Learning Algorithm
  • Understanding Unsupervised Learning Algorithm – K-means Clustering, Hierarchical Clustering and examples.