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Python for Data Science Bootcamp

Noble Desktop - Virtually Online

Uncover the power of Python for analyzing real-world data sets in this hands-on course at Noble Desktop. Explore Python fundamentals and learn how to create programs, work with data, visualize insights, and develop machine learning models. Elevate your data science skills with the Python for Data Science Bootcamp.

(372) All levels 18 and older
$1,495

5 sessions

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Python Developer Immersive

Practical Programming - Virtually Online

Embark on a transformative journey into the world of Python development with a comprehensive curriculum designed to elevate your coding skills to new heights.

(378) All levels 18 and older
$3,995

15 sessions

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Python Data Visualization & Interactive Dashboards

Noble Desktop - Virtually Online

Master the art of visualizing data and creating interactive dashboards using Python. Gain hands-on experience with popular libraries such as NumPy, Pandas, Matplotlib, Seaborn, Plotly, and Dash Enterprise. Impress potential employers with your data science skills by working on real-life projects and demonstrating your coding and analytical abilities.

(372) All levels 18 and older
$1,695

10 sessions

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Python for Data Science Immersive

Practical Programming - Virtually Online

Unlock the power of Python and dive into the world of data science with this immersive course. Gain practical skills in programming, data analysis, and visualization, and become a valuable asset in high-growth industries. Start your journey towards a career in data science today.

(378) Beginner 18 and older
$1,495

5 sessions

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Python Immersive

Practical Programming - Virtually Online

Immerse yourself in a hands-on beginner Python programming course to master programming fundamentals, create objects in Object-Oriented Programming, and tackle real-world challenges. Gain practical experience with coding exercises and build a portfolio of projects to showcase your skills.

(378) Beginner 18 and older
$1,495

5 sessions

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Data Science

Unlock the potential of data to drive informed decision-making and achieve business goals with cutting-edge techniques and tools to analyze data and extract valuable insights.

  • All levels
  • 18 and older
  • $16,900
  • Interactive Online Classroom
  • 675 hours over 75 sessions

Start Dates (3)

  • $16,900
  • Interactive Online Classroom
  • 675 hours over 75 sessions
Book
Show all 75 sessions
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Book
Show all 75 sessions
  • Mon, May 13 at 9:00am - 6:00pm
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Book
Show all 75 sessions
  • Mon, Jun 24 at 9:00am - 6:00pm
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Class Description

Description

What you'll learn in this data science course:

If accountability, a set schedule, and dedicated classmates match your learning style, we suggest learning full-time. But if you have a packed schedule and flexibility is what matters most to you, we recommend choosing our Flex program.

No matter which pace you pick, you'll learn our tried-and-true curriculum proven to help students land jobs and start promising data science careers.

Curriculum & Program Experience

Phase 1: Data Analysis and Engineering

You’ll learn basic Python programming, how to use Jupyter Notebooks, and will be familiarized with popular Python libraries that are used in data science. To organize your data, you’ll learn about data structures, relational databases, ways to retrieve data, and the fundamentals of SQL for data querying structured databases.

Items covered:

  • Variables
  • Booleans and Conditionals
  • Lists
  • Dictionaries
  • Looping
  • Functions
  • Data Structures
  • Data Cleaning
  • Pandas
  • NumPy
  • Matlotlib/Seaborn for Data Visualization
  • Git/Github
  • SQL
  • Accessing Data through APIs
  • Web Scraping

Phase 2: Scientific Computing and Quantitative Methods

You’ll learn about the fundamentals of probability theory like combinations and permutations. You'll also learn about statistical distributions and how to create samples, then apply this knowledge by running A/B experiments. Lastly, you'll build your first data science model using linear regression.

Items covered:

  • Combinatorics
  • Probability Theory
  • Statistical Distributions
  • Bayes Theorem
  • Sampling Methods
  • Hypothesis Testing
  • A/B Testing
  • Linear Regression
  • Model Evaluation

Phase 3: Machine Learning Fundamentals

You'll learn about regression analysis and a new form of regression: logistic regression. You'll also learn about penalization terms, preventing overfitting through regularization, and using cross-validation to validate regression models.  

Items covered:

  • Linear Algebra
  • Logistic regression
  • Maximum Likelihood Estimation
  • Optimization Cost Function
  • Pipeline Building
  • Hyperparameter Tuning
  • Grid Search
  • Scikit-Learn
  • Gradient Descent
  • K-Nearest Neighbors
  • Decision Trees
  • Ensemble Methods

Phase 4: Advanced Machine Learning

You'll be introduced to threading and multiprocessing to be able to work with big data.  In doing so, you’ll learn about PySpark and AWS, and how to use those tools to build a recommendation system.  You'll also learn about densely connected neural networks and sentiment analysis.

Items covered:

  • Dimensionality Reduction
  • Clustering
  • Times Series Analysis
  • Neural Networks
  • Big Data
  • Natural Language Processing
  • Text Vectorization
  • Natural Language Toolkit
  • Regular Expressions
  • Word2Vec
  • Text Classification
  • Recommendation  Systems
Phase 5: Data Science Project

In your final project, you’ll work individually to create a large-scale data science and machine learning project. This final project provides an in-depth opportunity for you to demonstrate your learning accomplishments and get a feel for what working on a large-scale data science project is really like.

Pick a start date that fits your schedule

In our full-time courses, you'll have access to a virtual classroom where you’ll interact with your instructors and fellow students on a fixed, full-time schedule: 9 hours a day, Monday through Friday, for 15 weeks.


Remote Learning

This course is available for "remote" learning and will be available to anyone with access to an internet device with a microphone (this includes most models of computers, tablets). Classes will take place with a "Live" instructor at the date/times listed below.

Upon registration, the instructor will send along additional information about how to log-on and participate in the class.

Refund Policy

Due to the high costs of hardware, software, facilities and staff resources a non-refundable, non-transferable 25% of tuition is required per course, per participant.

  • Payments, less the non-refundable amount, are refundable until 4 weeks (31 days) prior to the start of the confirmed course start date.
  • No refund will be issued for cancellations or withdrawals within the 31 days of the start of the confirmed course start date.
A $35 cancellation fee will be applied to all refunds.

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