Welcome to the world of Data Science! This course is designed to provide you with a solid foundation in the essential concepts, tools, and techniques used in data science. Whether you’re completely new to data analysis or looking to enhance your skills in statistical analysis, machine learning, and data visualization, this course will equip you with the necessary knowledge to extract insights from data and make informed decisions.

Learning Objectives:

Students will gain a comprehensive understanding of core concepts such as data wrangling, exploratory data analysis, statistical inference, and predictive modeling. They will develop practical skills in collecting, cleaning, and preparing data, as well as using programming languages like Python or R and relevant libraries for data manipulation and analysis. The course will enhance their ability to explore and visualize data, apply statistical and machine learning methods, and evaluate models effectively. Additionally, students will learn to communicate data-driven insights clearly, address ethical considerations in data practices, and apply their knowledge to real-world problems through hands-on projects and case studies.

Prerequisites:

• Basic Programming Skills ideally Python or R
• Mathematics and Statistics
• Data Handling Knowledge
• Analytical Thinking
• Familiarity with Excel

Materials Needed:

• Computer with internet access.
• Basic familiarity with using Python (installation instructions provided).
• Headphones.

Who Should Take This Course:

• Aspiring data scientists looking to start a career in data analysis and machine learning.
• Analysts and professionals seeking to enhance their data analysis skills.
• Business managers and decision-makers interested in leveraging data for strategic decision-making.
• Anyone interested in exploring the intersection of programming, statistics, and machine learning.

Key Outcome:

• Have a strong understanding of core data science concepts and techniques.
• Be proficient in using Python and popular libraries for data manipulation, analysis, and visualization.
• Be able to perform statistical analysis, apply machine learning algorithms, and evaluate model performance.
• Have completed a capstone project demonstrating your ability to tackle real-world data science challenges.

Assessment:
Assessment will be based on completion of projects, participation in class activities, and a final project showcase.

Certification: Certificate of completion provided upon finishing the course requirements.

Course Duration: 32 credit hours – 4 months

Days & Timings: One-Hour Interactive Class, Twice a Week (Flexible Timings)

Course Format: Normal Track – 2 hours per week, Fast Track – 4 hours per week

Eligible Age Group: 14 and above

Fee: Monthly – USD 120 | Full Course – USD 400  

Instructor:

Embark on your journey into data science and unlock the power of data-driven decision-making!