Data Science for Marketing Analytics Training

Nivå: Intermediate

This data science for marketing analytics course starts by teaching you how to use Python libraries, such as pandas and Matplotlib, to read data from Python, manipulate it, and create plots, using both categorical and continuous variables. Then, you'll learn how to segment a population into groups and use different clustering techniques to evaluate customer segmentation. As you make your way through the chapters of this marketing analytics course, you'll explore ways to evaluate and select the best segmentation approach and go on to create a linear regression model on customer value data to predict lifetime value.

In the concluding chapters, you'll gain an understanding of regression techniques and tools for evaluating regression models and explore ways to predict customer choice using classification algorithms. Finally, you'll apply these techniques to create a churn model for modelling customer product choices.

Nyckelfunktioner:

  • After-course instructor coaching benefit

Du kommer lära dig att:

  • Work with a raw data set.
  • Segment and model a population.
  • Build your own marketing reporting and interactive dashboards.

Välj den utbildningsform som passar dig bäst

LIVE, LÄRARLEDD

I klass & Live, Online-utbildning

  • 3-day instructor-led training course
  • One-on-one after-course instructor coaching
  • Pay later by invoice -OR- at the time of checkout by credit card

UTBILDNING PÅ DIN WEBBPLATS

Teamträning

  • Använd denna eller någon annan utbildning i ditt företag
  • Fullskalig programutveckling
  • Levereras när, var och hur du vill
  • Blandade utbildningsmodeller
  • Skräddarsytt innehåll
  • Coaching av ett expertteam

Anpassa kurs och innehåll efter teamets behov

Kontakta oss

Utveckla dig och ditt team med anpassade eller öppna kurser alternativt e-learning

Learning Tree erbjuder kundanpassad utbildning hos er, öppna kurser i Stockholm, London eller Washington, möjlighet att delta via våra Anywhere centers (Malmö, Göteborg, Linköping, Stockholm eller Borlänge) eller olika former av e-learning med lärarstöd. Läs mer på www.learningtree.se/priser .

I klass & Live, Online-utbildning

Note: This course runs for 3 dagar

  • 31 mar - 2 apr 9:00 - 4:30 BST London / Online (AnyWare) London / Online (AnyWare) Boka Din Kursplats

  • 23 - 25 jun 9:00 - 4:30 BST London / Online (AnyWare) London / Online (AnyWare) Boka Din Kursplats

  • 7 - 9 okt 9:00 - 4:30 BST London / Online (AnyWare) London / Online (AnyWare) Boka Din Kursplats

  • 8 - 10 jan 9:00 - 4:30 EST New York / Online (AnyWare) New York / Online (AnyWare) Boka Din Kursplats

  • 12 - 14 feb 9:00 - 4:30 EST Ottawa / Online (AnyWare) Ottawa / Online (AnyWare) Boka Din Kursplats

  • 26 - 28 feb 9:00 - 4:30 EST Herndon, VA / Online (AnyWare) Herndon, VA / Online (AnyWare) Boka Din Kursplats

  • 1 - 3 apr 9:00 - 4:30 EDT New York / Online (AnyWare) New York / Online (AnyWare) Boka Din Kursplats

  • 13 - 15 maj 9:00 - 4:30 EDT Ottawa / Online (AnyWare) Ottawa / Online (AnyWare) Boka Din Kursplats

  • 3 - 5 jun 9:00 - 4:30 EDT Herndon, VA / Online (AnyWare) Herndon, VA / Online (AnyWare) Boka Din Kursplats

  • 8 - 10 jul 9:00 - 4:30 EDT New York / Online (AnyWare) New York / Online (AnyWare) Boka Din Kursplats

  • 19 - 21 aug 9:00 - 4:30 EDT Ottawa / Online (AnyWare) Ottawa / Online (AnyWare) Boka Din Kursplats

  • 2 - 4 sep 9:00 - 4:30 EDT Herndon, VA / Online (AnyWare) Herndon, VA / Online (AnyWare) Boka Din Kursplats

Kurs med startgaranti

När du ser symbolen för “Guaranteed to Run” vid ett kurstillfälle vet du att kursen blir av. Garanterat.

Data Science for Marketing Analytics Training Information

  • Who Should Attend

    Data Science for Marketing Analytics is designed for developers and marketing analysts looking to use new, more sophisticated tools in their marketing analytics efforts. It'll help if you have prior experience of coding in Python and knowledge of high school level mathematics. Some experience with databases, Excel, statistics, or Tableau is useful but not necessary

Data Science for Marketing Analytics Training Outline

  • Lesson 1: Data Preparation and Cleaning

    • Data Models and Structured Data
    • Pandas
    • Data Manipulation
  • Lesson 2: Data Exploration and Visualisation

    • Identifying the Right Attributes
    • Generating Targeted Insights
    • Visualising Data
  • Lesson 3: Unsupervised Learning: Customer Segmentation

    • Customer Segmentation Methods
    • Similarity and Data Standardization
    • k-means Clustering
  • Lesson 4: Choosing the Best Segmentation Approach

    • Choosing the Number of Clusters
    • Different Methods of Clustering
    • Evaluating Clustering
  • Lesson 5: Predicting Customer Revenue Using Linear Regression

    • Understanding Regression
    • Feature Engineering for Regression
    • Performing and Interpreting Linear Regression
  • Lesson 6: Other Regression Techniques and Tools for Evaluation

    • Evaluating the Accuracy of a Regression Model
    • Using Regularization for Feature Selection
    • Tree-Based Regression Models
  • Lesson 7: Supervised Learning: Predicting Customer Churn

    • Classification Problems
    • Understanding Logistic Regression
    • Creating a Data Science Pipeline
  • Lesson 8: Fine-Tuning Classification Algorithms

    • Support Vector Machine
    • Decision Trees
    • Random Forest
    • Preprocessing Data for Machine Learning Models
    • Model Evaluation
    • Performance Metrics
  • Lesson 9: Modelling Customer Choice

    • Understanding Multiclass Classification
    • Class Imbalanced Data

Teamträning

Data Science for Marketing Analytics FAQs

  • Can I take this data marketing analytics course online?

    Yes! We know your busy work schedule may prevent you from getting to one of our classrooms which is why we offer convenient online training to meet your needs wherever you want, including online training.

London / Online (AnyWare)
London / Online (AnyWare)
London / Online (AnyWare)
New York / Online (AnyWare)
Ottawa / Online (AnyWare)
Herndon, VA / Online (AnyWare)
New York / Online (AnyWare)
Ottawa / Online (AnyWare)
Herndon, VA / Online (AnyWare)
New York / Online (AnyWare)
Ottawa / Online (AnyWare)
Herndon, VA / Online (AnyWare)
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