Introduction to Data Science with Python
Overview
At Canadian College Of Business Health And Arts, we recognize and harness the transformative power of customized guidance and strategic insight to propel both individuals and organizations towards their objectives.
Whether you are a seasoned executive or a budding entrepreneur, our services are meticulously crafted to meet you at your current stage and facilitate your progress toward your aspirations.
Acknowledging the unique landscape of each business, along with its distinct challenges and opportunities, we adopt a tailored approach, collaborating closely with you to devise strategies that directly address your specific requirements and foster substantial advancement.
Our mission is to empower you with the essential tools, knowledge, and confidence necessary to navigate complex business environments and attain sustainable success. Our commitment transcends conventional coaching techniques, integrating an array of proven methods and innovative practices to provide comprehensive support.
From strategic planning and leadership development to enhancing team dynamics and performance, our expertise encompasses diverse facets of business management. We take pride in cultivating a collaborative and supportive atmosphere where you are encouraged to explore new concepts, overcome challenges, and unlock your full potential.
With a history of success and an unwavering dedication to excellence, we stand ready to partner with you on your journey toward growth and achievement, transforming your vision into reality and laying the groundwork for enduring success.
What You’ll Learn
In this course, you’ll learn how to leverage the Python programming language to analyze and visualize data, and apply statistical methods to extract insights. Key concepts covered include:
- Data manipulation with libraries such as Pandas
- Visualization techniques using Matplotlib and Seaborn
- Applying machine learning models using scikit-learn
- Working with real-world datasets to perform exploratory data analysis (EDA)
- Understanding data preprocessing, feature engineering, and model evaluation
By the end of the course, you’ll be equipped to tackle a variety of data-driven challenges and build your own data science projects from scratch.
Job Opportunities: Upon completion of this course, you’ll be ready to pursue roles such as:
- Data Analyst
- Junior Data Scientist
- Data Engineer
- Machine Learning Engineer
- Business Intelligence Analyst
- Research Scientist (in fields such as healthcare, finance, or marketing)
- Data Science Intern
Data science is one of the fastest-growing fields, with companies in nearly every industry seeking skilled professionals to analyze their data and drive decision-making processes.
Chapters
-
Introduction to Data Science
-
Python Basics for Data Science
-
Data Wrangling and Preprocessing
-
Exploratory Data Analysis (EDA)
-
Statistical Analysis in Python
-
Introduction to Machine Learning
-
Model Evaluation and Improvement
-
Mini Project
Students are required to complete 39 hours of in-class training.
39 hours
Program Summary
This table will display a summary of total instructional hours, delivery format and percentage weight for every Type of Learning entered in the List of Subjects. The ministry, career college and any subject or education assessors may refer to this section for a general understanding of the components of the program.
| Type of Learning | Total Instruction Hours | Delivery Format | % Weight |
|---|---|---|---|
| Theory | 20.00 | On-Line | 58.67% |
| Practical | 19.00 | On-Line | 41.33% |
| Total Type of Learning | 39.00 | ||
| Total Program Hours | 39.00 | 100.00% |
$CAD
Details
Certification
39 Hours
Updated: 03/01/2025
Prerequisites
If you attended a post-secondary institution after high school, we need both your high school transcript and your post-secondary transcript.
- Entry into many of our programs is competitive and your post-secondary marks can strengthen your application.
- If you did not graduate from high school and have a GED, send us a copy.
- Even if you graduated a while ago, we still need your high school transcript.
- If you cannot obtain it, let us know and we can discuss your options.
- If you studied at college or university, you must submit your post-secondary transcript AND
your high-school transcript. This may strengthen your application.
- Basic understanding of machine learning concepts.
- Familiarity with Python programming and libraries like TensorFlow or PyTorch.
- Understanding of neural networks and deep learning fundamentals.
Get In Touch or Create an Account
Ready to Get Started?
Vivamus suscipit tortor eget felis porttitor volutpat. Lorem ipsum dolor sit amet, consectetur adipiscing elit.