Certification Course in Data Science

Overview

Credge presents a cutting-edge Data Science program tailored for high school students. This program empowers participants to delve into the intricacies of data analysis, grasp statistical modeling concepts, and master various regression techniques.
Beyond theoretical understanding, students get hands-on experience by applying their data science knowledge in innovative projects such as creating chatbots and implementing human speech recognition.
This comprehensive approach not only equips students with essential skills in the burgeoning field of data science but also encourages practical application, fostering creativity and problem-solving abilities essential for real-world scenarios. Elevate your understanding and skills in data science with Credge specially crafted program.

Why Choose this Program?

1. Embark on a data science program for unparalleled career opportunities, as data-driven decision-making becomes crucial across industries.
2. Gain expertise in data analysis, statistical modeling, and machine learning, fostering a versatile skill set crucial for modern industries.
3. Explore practical projects like chatbots and speech recognition, translating theoretical knowledge into tangible skills applicable in diverse professional scenarios.
4. Elevate problem-solving skills and creativity, as data science empowers you to unlock insights, drive innovation, and make informed decisions in various domains.

Salient Features of This Program

• Tailored for 8th to 12th Graders
• Practical Learning Opportunity
• Interactive Learning

You Get A Completion Certificate

Upon successfully finishing the Data Science Certification Course, students will obtain a
prestigious certificate, validating their mastery in Data Science. This certification
enhances career prospects and unlocks various opportunities 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.