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Data Science With Python Foundation

We recognise that Python is one of the most essential skills required by a Data Scientist. Therefore, we have built a course that gives you the in-depth knowledge of data science using Python. So if you are looking to become a successful and a well-informed Data Scientist, this course is for you. Explore the vast world of data science and the applications of AI in the present market and take the much needed step of your career.

Schedules

Overview


Starting from the basics and learning valuable skill-set with every step is the basis of this course; learning the functioning of Jupyter Notebooks, moving to pandas, train models, Matplotlib, NumPy Seaborn. Whether you are a beginner or advanced in your field, you will be able to gain additional, relevant information through this training.

You will be trained to present your code in a clear format, enabling anyone reading your code to understand its meaning. This will help in visualization and creating plots. The course will give you a blend of practical and theoretical, enabling you to be resourceful and excel in the real-world scenario. At the end of this course, every twist and turn of the world of data science using Python will be on your tips.

Course Curriculum


Working with Jupyter notebooks in a sustainable way.

How to do numerical computations and linear algebra with NumPy.

Visualizing data with Matplotlib, Seaborn, and other packages.

Transforming and munging data with pandas.

ML concepts

  • Why and when to use ML
  • Types of Learning tasks & ML approaches

ML Theory

  • Why and when to use ML
  • Types of Learning tasks & ML approaches

ML Theory

  • Optimisation with gradient descent
  • Under/Overfitting, Generalisation & Regularization

Introduction to Scikit-Learn

  • Training & evaluating a Scikit-Learn estimator
  • Interpreting a Scikit-Learn model

Overview of ML algorithms

  • Pros & Cons of the most common ML models
  • How to choose an appropriate ML model

Scikit-learn Pipelines

  • Preprocessing with Scikit-Learn transformers
  • Cross-validation and hyperparameter searches

Hackathon.

Data Science with Python Foundation exam

Prerequisite


Python for Data Analysts is a foundation training; previous knowledge of Python is required. This training requires a laptop. The hands-on labs are run in an online environment, eliminating the need to install software.

Certification


We have worked together with APMG International to offer you a recognized partner to get certified in Data Science for Product Owners. The exam and Data Science with Python Foundation certificate are included in the course. The exam can be taken directly after the training or at a moment of your choice. If you get at least 50% of the 50 multiple choice questions right, you will pass the exam and receive your certificate. 

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