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Data Science & Machine Learning Foundations
Learning PathData Science & Machine Learning Foundations

This path is for anyone looking for an intuitive introduction to the world of data science, including profiling, classification, regression & unsupervised machine learning

15 hours
4 courses
0 projects
Overview

This path is for anyone looking to develop a strong, foundational understanding of popular machine learning tools and techniques.

Unlike most data science or ML courses, this is NOT about learning how to code with Python or R. Instead, we'll use familiar, intuitive tools like Microsoft Excel to break down complex models and visualize exactly how they work.

We'll start by introducing the machine learning landscape and workflow, and exploring common univariate & multivariate data profiling techniques like frequency tables, histograms, heat maps, scatter plots and more.

Next we'll dive into the world of supervised learning, and review key concepts like dependent vs. independent variables, feature engineering, splitting and overfitting. In course #2, we'll introduce powerful classification models, including decision trees, logistic regression, and K-nearest neighbors.

From there we'll cover the building blocks of regression modeling and time-series forecasting, and explore powerful techniques for identifying seasonality, predicting nonlinear trends, and measuring the impact of key business decisions using intervention analysis.

Last but not least we'll introduce the world of unsupervised learning, and break down powerful unsupervised techniques including cluster analysis, association mining, outlier detection, and dimensionality reduction.

If you’re ready to build the foundation for a successful career in data science, this is the course for you.

WHO SHOULD TAKE THIS PATH?

  • Anyone looking to learn the basics of machine learning through real-world demos and intuitive, crystal clear explanations
  • Data Analysts or BI experts looking to transition into data science or build a fundamental understanding of machine learning
  • R or Python users seeking a deeper understanding of the models and algorithms behind their code

WHAT ARE THE PATH REQUIREMENTS?

  • This is a beginner-friendly course (no prior knowledge or math/stats background required)
  • We'll use Microsoft Excel (Office 365) for course demos, but participation is optional
Curriculum
Course
Machine Learning 1: Data ProfilingExplore and prepare raw data for machine learning, and apply a range of univariate & multivariate data profiling techniques
Course
Machine Learning 2: ClassificationLearn powerful classification models for data-driven predictions, including decision trees, logistic regression, KNN, and more
Course
Machine Learning 3: RegressionExplore the building blocks of regression and time-series forecasting, and learn how to apply them to real-world projects
Course
Machine Learning 4: Unsupervised LearningLearn the basics of Unsupervised ML, including cluster analysis, association mining, outlier detection & dimensionality reduction
Instructors
Chris Dutton
Chris DuttonChris is an EdTech entrepreneur and best-selling Data Analytics instructor. As Founder and Chief Product Officer at Maven Analytics, his work has been featured by USA Today, Business Insider, Entrepreneur and the New York Times, reaching more than 1,000,000 students around the world.

Josh MacCarty
Josh MacCartyJosh brings over a decade of applied Machine Learning experience to the Maven team, specializing in forecasting, predictive modeling, natural language processing, cluster analysis, and pricing optimization. He has a Bachelors degree in Economics and was a Graduate Fellow for his Master's degree in Global Political Economy.
Overview

This path is for anyone looking to develop a strong, foundational understanding of popular machine learning tools and techniques.

Unlike most data science or ML courses, this is NOT about learning how to code with Python or R. Instead, we'll use familiar, intuitive tools like Microsoft Excel to break down complex models and visualize exactly how they work.

We'll start by introducing the machine learning landscape and workflow, and exploring common univariate & multivariate data profiling techniques like frequency tables, histograms, heat maps, scatter plots and more.

Next we'll dive into the world of supervised learning, and review key concepts like dependent vs. independent variables, feature engineering, splitting and overfitting. In course #2, we'll introduce powerful classification models, including decision trees, logistic regression, and K-nearest neighbors.

From there we'll cover the building blocks of regression modeling and time-series forecasting, and explore powerful techniques for identifying seasonality, predicting nonlinear trends, and measuring the impact of key business decisions using intervention analysis.

Last but not least we'll introduce the world of unsupervised learning, and break down powerful unsupervised techniques including cluster analysis, association mining, outlier detection, and dimensionality reduction.

If you’re ready to build the foundation for a successful career in data science, this is the course for you.

WHO SHOULD TAKE THIS PATH?

  • Anyone looking to learn the basics of machine learning through real-world demos and intuitive, crystal clear explanations
  • Data Analysts or BI experts looking to transition into data science or build a fundamental understanding of machine learning
  • R or Python users seeking a deeper understanding of the models and algorithms behind their code

WHAT ARE THE PATH REQUIREMENTS?

  • This is a beginner-friendly course (no prior knowledge or math/stats background required)
  • We'll use Microsoft Excel (Office 365) for course demos, but participation is optional
Instructors
Chris Dutton
Chris DuttonChris is an EdTech entrepreneur and best-selling Data Analytics instructor. As Founder and Chief Product Officer at Maven Analytics, his work has been featured by USA Today, Business Insider, Entrepreneur and the New York Times, reaching more than 1,000,000 students around the world.

Josh MacCarty
Josh MacCartyJosh brings over a decade of applied Machine Learning experience to the Maven team, specializing in forecasting, predictive modeling, natural language processing, cluster analysis, and pricing optimization. He has a Bachelors degree in Economics and was a Graduate Fellow for his Master's degree in Global Political Economy.
Curriculum
Course
Machine Learning 1: Data ProfilingExplore and prepare raw data for machine learning, and apply a range of univariate & multivariate data profiling techniques
Course
Machine Learning 2: ClassificationLearn powerful classification models for data-driven predictions, including decision trees, logistic regression, KNN, and more
Course
Machine Learning 3: RegressionExplore the building blocks of regression and time-series forecasting, and learn how to apply them to real-world projects
Course
Machine Learning 4: Unsupervised LearningLearn the basics of Unsupervised ML, including cluster analysis, association mining, outlier detection & dimensionality reduction
Testimonials

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"Thinking like an analyst" course is a very complete compact course if you have to go through the process of getting to know your customers business till building an insightful dashboard for them. I did a lot of courses the past year but this one is totally different. Key is satisfying your customer by giving them strong insights. I really enjoyed the course and put it on pause many times to check or use it directly in my own ongoing project. I can recommend this course to anybody working as a consultant in the data area.
Marjolein Opsteegh
Marjolein Opsteegh
Marjolein Opsteegh
Maven's Pivot Table & Charts class was a great intro to dashboard design but Advanced Excel Dashboard Design will take your approach to a whole new level. You'll learn the importance of formula-based dashboard design and how to manipulate colors, charts, and KPI metric cards to tell your story. By far one of my favorite Maven classes!
Nate Dunn
Nate Dunn
Thinking like an Analyst course has helped me to clearly understand what it takes to have a successful career in data analytics. I have learnt that my focus should be on the skills I acquire while learning and not the tools. I have also learnt a data analysis workflow for high quality analysis that drives actionable outcomes. I had fun while learning during this course. It is self pacing and elaborate.
Eniola Dada
Eniola Dada
Eniola Dada
For all aspiring or converted analyst out there, stop looking around, this is the way to get the role you are looking for. I am truly impressed with the quality of the information and the completeness of the package Maven Analytics put together. In this well rounded package you have everything you need, from finding your own path, writing or re-writing your resume, marketing on LinkedIn, to building the so needed project portfolio, and even interview skills and approaches.
Radu Tecuceanu
Radu Tecuceanu
Radu Tecuceanu
Love the Maven courses! The instructors always have great slide content to help solidify the concepts and drive home the key aspects. The examples and very relatable making it so much easier to understand how to apply my own projects.
Joseph Collins
Joseph Collins
Joseph Collins
Maven Analytics changed my life, I found a better job position taking the Excel and Power BI paths, nowadays I can apply my skills in my company innovating everyday. Thankful forever.
Rodrigo Chavez
Rodrigo Chavez
Rodrigo Chavez
An excellent course with top-notch data sets to work around with. As usual, Chris Dutton did a fabulous job of covering each element with a simplistic but analytical approach. Although I've been using pivot tables for 5+ years, the new learnings will open a whole array of opportunities for extracting actionable insights. Thank you!
Faizan Qadri
Faizan Qadri
Faizan Qadri
Before deciding to join this learning platform, I struggled to understand and figure out what direction I needed to take for my skill development to be a Data Analyst. This first course helped ease some of my fears and confusion. I am more passionate about my decision to become a data analyst. THANK YOU Chris, John, Aaron, and Enrique , and I look forward to learning more through Maven.
Angie
Angie
Angie
The Maven Analytics Courses are packed full of practical lessons and useful pro tips that can be immediately applied to data in the workplace. One of the best trainings I've ever taken!
Randy McCauley
Randy McCauley
Randy McCauley
Once again Maven blows it out of the water. In this fantastic, well structures course about the way to "Think Like an Analyst". It has so many good points and actions to take when putting together a project. I found it very useful and was able to put it into practice at work straight away. Thank Guys!
Catherine Taylor
Catherine Taylor
Catherine Taylor
Maven really makes it possible to get into data analytics without taking (and paying for) a traditional education program. The courses I took left me with a better understanding and deeper knowledge of what I like most: analyzing data.
Erik van’t Ende
Erik van’t Ende
Erik van’t Ende
The course is fantastic and highly recommended. It gave me the confidence to perform the logical analysis in any given data source and of course build kickass visuals business dashboards for my clients :). Loved the course from the first second to the last.
Tonmoy Hashmi
Tonmoy Hashmi
Tonmoy Hashmi
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