Python Data Science & Machine Learning Bootcamp
IDCML

Hands-on Training from Experts Live Online

Build hands-on skills in Python programming, data analysis, and machine learning using libraries like pandas, scikit-learn, and TensorFlow. You'll work on real-world projects, explore data visualization techniques, and gain experience cleaning and modeling data for practical applications.

This program includes

  • 96 hours of live, project-based training from experts
  • Software Access
  • Additional 1-on-1 mentoring outside of class
  • Access to class recordings (30 days)
  • Verified digital certificate of completion
  • Learn at an accredited institution

Become a Python Programmer

Gain the skills to apply Python in data science, machine learning, data visualization, and automation. In this program, you’ll develop the programming expertise needed to work with databases and perform various levels of data analysis. By the end, you’ll be ready to apply for entry-level roles in data science and Python development.

Dive into Machine Learning & Automation

Start with Python programming fundamentals, then use NumPy, Pandas, and Matplotlib to analyze data. After mastering Python and its three core data science libraries, you’ll build predictive models with machine learning tools like scikit-learn. You’ll also leverage Python for automation, streamlining tasks such as aggregating, updating, and formatting data.

Create Dashboards & Visualizations with Real-Life Data

In the final module, work with Matplotlib, Seaborn, Plotly, and Dash to design data visualizations and interactive dashboards. You’ll deploy your projects to GitHub, making them easily accessible for potential employers to view.

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Add additional skills with another certificate program:

Courses in this Certificate Program

This is the recommended order, but some courses may be taken in a different order.

Download Syllabus PDF

Unit 1 30 Hours

Python for Data Science Bootcamp
  • Learn Python fundamentals, including variables, data types, functions, loops, and control flow, for building robust programs
  • Work with complex data structures such as dictionaries and lists to efficiently organize and access data
  • Use NumPy and Pandas to import, clean, and manipulate datasets for analysis and exploration
  • Generate descriptive statistics and apply filtering, grouping, and pivoting techniques to gain deeper insights
  • Visualize data using Matplotlib and create clear, customized charts, including bar graphs, histograms, and scatter plots
  • Gain the practical skills needed to transition into machine learning with a solid understanding of data science workflows

Unit 2 30 Hours

Python Machine Learning Bootcamp
  • Explore foundational techniques like linear and logistic regression for modeling numerical and categorical data
  • Understand the difference between regression and classification problems and when to apply each approach
  • Build and evaluate models using k-nearest neighbors, decision trees, and ensemble methods like random forest
  • Learn key concepts such as cross-validation, training vs. test sets, and performance metrics like mean squared error
  • Apply feature engineering techniques to improve model accuracy while managing overfitting and bias-variance tradeoffs
  • Use Python's essential data science libraries, NumPy, Pandas, and scikit-learn, to structure data and implement algorithms
  • Gain insights into how machine learning powers systems at companies like Netflix, Spotify, and Amazon
  • Complete a final portfolio project that demonstrates your ability to apply machine learning to solve real problems

Unit 3 6 Hours

Python for Automation
  • Understand how websites are structured with HTML and CSS to identify elements for data extraction
  • Learn Python fundamentals, such as variables, data types, conditionals, loops, and list manipulation
  • Use the Requests and Beautiful Soup libraries to perform web scraping and target specific content
  • Write loops to automate web scraping across multiple pages and streamline repetitive tasks
  • Store scraped data in different formats, such as text files and CSVs, for analysis and reporting
  • Schedule Python scripts to run on a regular basis, enabling continuous data collection and automating workflows

Unit 4 24 Hours

Python Data Visualization & Interactive Dashboards

Transform raw data into interactive visual insights by building dashboards with Python’s top visualization tools. This course blends analysis, design, and deployment to help you showcase data professionally.

  • Work with real-life datasets using Python’s core libraries, including NumPy for numerical computing and Pandas for data manipulation
  • Create static and interactive visualizations using Matplotlib, Seaborn, and Plotly to clearly communicate trends and patterns
  • Build multi-component dashboards using Dash Enterprise, incorporating callbacks, sliders, date pickers, and more
  • Practice hands-on development by applying new skills to personalized projects with guided instructor support
  • Publish your dashboards online using GitHub and Heroku to demonstrate your work to potential employers or clients
  • Explore best practices for styling and structuring visual narratives that are clear, persuasive, and engaging

Schedule & Enrollment: Python Data Science & Machine Learning Bootcamp

  • 96 Hours
  • Price before discounts: $5,510 Full tuition: $3,495
  • Live Online
  • Payment plans
  • Software Access
  • 1:1 Mentoring included

  • Custom Schedule
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  • August 19–December 11 Show package courses
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  • September 8–30 Show package courses
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  • September 8–30 Show package courses
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  • October 27–November 14 Show package courses
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  • December 1–19 Show package courses
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  • December 14–March 29 Show package courses
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