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Register on the Data Science and Machine Learning using Python : A Bootcamp today and build the experience, skills and knowledge you need to enhance your professional development and work towards your dream job. Study this course through online learning and take the first steps towards a long-term career.

The course consists of a number of easy to digest, in-depth modules, designed to provide you with a detailed, expert level of knowledge. Learn through a mixture of instructional video lessons and online study materials.

Receive online tutor support as you study the course, to ensure you are supported every step of the way. Get a free e-certificate as proof of your course completion.

The Data Science and Machine Learning using Python : A Bootcamp is incredibly great value and allows you to study at your own pace. Access the course modules from any internet-enabled device, including computers, tablet, and smartphones.

The course is designed to increase your employability and equip you with everything you need to be a success. Enrol on the now and start learning instantly!

What You Get With The Data Science and Machine Learning using Python : A Bootcamp
  • Receive a free e-certificate upon successful completion of the course
  • Get taught by experienced, professional instructors
  • Study at a time and pace that suits your learning style
  • Get instant feedback on assessments 
  • 24/7 help and advice via email or live chat
  • Get full tutor support on weekdays (Monday to Friday)

Course Design

The course is delivered through our online learning platform, accessible through any internet-connected device. There are no formal deadlines or teaching schedules, meaning you are free to study the course at your own pace.

You are taught through a combination of

  • Video lessons
  • Online study materials

Certification

Upon successful completion of the course, you will be able to obtain your course completion e-certificate free of cost. Print copy by post is also available at an additional cost of 9.99 and PDF Certificate at 4.99.

Who Is This Course For:

The course is ideal for those who already work in this sector or are an aspiring professional. This course is designed to enhance your expertise and boost your CV. Learn key skills and gain a professional qualification to prove your newly-acquired knowledge.

Requirements:

The online training is open to all students and has no formal entry requirements. To study the Data Science and Machine Learning using Python : A Bootcamp, all your need is a passion for learning, a good understanding of English, numeracy, and IT skills. You must also be over the age of 16.

Course Curriculum

Welcome, Course Introduction & overview, and Environment set-up
Welcome & Course Overview 00:07:00
Set-up the Environment for the Course (lecture 1) 00:09:00
Set-up the Environment for the Course (lecture 2) 00:25:00
Two other options to setup environment 00:04:00
Python Essentials
Python data types Part 1 00:21:00
Python Data Types Part 2 00:15:00
Loops, List Comprehension, Functions, Lambda Expression, Map and Filter (Part 1) 00:16:00
Loops, List Comprehension, Functions, Lambda Expression, Map and Filter (Part 2) 00:20:00
Python Essentials Exercises Overview 00:02:00
Python Essentials Exercises Solutions 00:22:00
Python for Data Analysis using NumPy
What is Numpy? A brief introduction and installation instructions. 00:03:00
NumPy Essentials – NumPy arrays, built-in methods, array methods and attributes. 00:28:00
NumPy Essentials – Indexing, slicing, broadcasting & boolean masking 00:26:00
NumPy Essentials – Arithmetic Operations & Universal Functions 00:07:00
NumPy Essentials Exercises Overview 00:02:00
NumPy Essentials Exercises Solutions 00:25:00
Python for Data Analysis using Pandas
What is pandas? A brief introduction and installation instructions. 00:02:00
Pandas Introduction 00:02:00
Pandas Essentials – Pandas Data Structures – Series 00:20:00
Pandas Essentials – Pandas Data Structures – DataFrame 00:30:00
Pandas Essentials – Handling Missing Data 00:12:00
Pandas Essentials – Data Wrangling – Combining, merging, joining 00:20:00
Pandas Essentials – Groupby 00:10:00
Pandas Essentials – Useful Methods and Operations 00:26:00
Pandas Essentials – Project 1 (Overview) Customer Purchases Data 00:08:00
Pandas Essentials – Project 1 (Solutions) Customer Purchases Data 00:31:00
Pandas Essentials – Project 2 (Overview) Chicago Payroll Data 00:04:00
Pandas Essentials – Project 2 (Solutions Part 1) Chicago Payroll Data 00:18:00
Python for Data Visualization using matplotlib
Matplotlib Essentials (Part 1) – Basic Plotting & Object Oriented Approach 00:13:00
Matplotlib Essentials (Part 2) – Basic Plotting & Object Oriented Approach 00:22:00
Matplotlib Essentials (Part 3) – Basic Plotting & Object Oriented Approach 00:22:00
Matplotlib Essentials – Exercises Overview 00:06:00
Matplotlib Essentials – Exercises Solutions 00:21:00
Python for Data Visualization using Seaborn
Seaborn – Introduction & Installation 00:04:00
Seaborn – Distribution Plots 00:25:00
Seaborn – Categorical Plots (Part 1) 00:21:00
Seaborn – Categorical Plots (Part 2) 00:16:00
Seborn-Axis Grids 00:25:00
Seaborn – Matrix Plots 00:13:00
Seaborn – Regression Plots 00:11:00
Seaborn – Controlling Figure Aesthetics 00:10:00
Seaborn – Exercises Overview 00:04:00
Seaborn – Exercise Solutions 00:19:00
Python for Data Visualization using pandas
Pandas Built-in Data Visualization 00:34:00
Pandas Data Visualization Exercises Overview 00:03:00
Panda Data Visualization Exercises Solutions 00:13:00
Python for interactive & geographical plotting using Plotly and Cufflinks
Plotly & Cufflinks – Interactive & Geographical Plotting (Part 1) 00:19:00
Plotly & Cufflinks – Interactive & Geographical Plotting (Part 2) 00:14:00
Plotly & Cufflinks – Interactive & Geographical Plotting Exercises (Overview) 00:11:00
Plotly & Cufflinks – Interactive & Geographical Plotting Exercises (Solutions) 00:37:00
Capstone Project - Python for Data Analysis & Visualization
Project 1 – Oil vs Banks Stock Price during recession (Overview) 00:15:00
Project 1 – Oil vs Banks Stock Price during recession (Solutions Part 1) 00:18:00
Project 1 – Oil vs Banks Stock Price during recession (Solutions Part 2) 00:18:00
Project 1 – Oil vs Banks Stock Price during recession (Solutions Part 3) 00:17:00
Project 2 (Optional) – Emergency Calls from Montgomery County, PA (Overview) 00:03:00
Python for Machine Learning (ML) - scikit-learn - Linear Regression Model
Introduction to ML – What, Why and Types….. 00:15:00
Theory Lecture on Linear Regression Model, No Free Lunch, Bias Variance Tradeoff 00:15:00
scikit-learn – Linear Regression Model – Hands-on (Part 1) 00:17:00
scikit-learn – Linear Regression Model Hands-on (Part 2) 00:19:00
Good to know! How to save and load your trained Machine Learning Model! 00:01:00
scikit-learn – Linear Regression Model (Insurance Data Project Overview) 00:08:00
scikit-learn – Linear Regression Model (Insurance Data Project Solutions) 00:30:00
Python for Machine Learning - scikit-learn - Logistic Regression Model
Theory: Logistic Regression, conf. mat., TP, TN, Accuracy, Specificity…etc. 00:10:00
scikit-learn – Logistic Regression Model – Hands-on (Part 1) 00:17:00
scikit-learn – Logistic Regression Model – Hands-on (Part 2) 00:20:00
scikit-learn – Logistic Regression Model – Hands-on (Part 3) 00:11:00
scikit-learn – Logistic Regression Model – Hands-on (Project Overview) 00:05:00
scikit-learn – Logistic Regression Model – Hands-on (Project Solutions) 00:15:00
Python for Machine Learning - scikit-learn - K Nearest Neighbors
Theory: K Nearest Neighbors, Curse of dimensionality …. 00:08:00
scikit-learn – K Nearest Neighbors – Hands-on 00:25:00
scikt-learn – K Nearest Neighbors (Project Overview) 00:04:00
scikit-learn – K Nearest Neighbors (Project Solutions) 00:14:00
Python for Machine Learning - scikit-learn - Decision Tree and Random Forests
Theory: D-Tree & Random Forests, splitting, Entropy, IG, Bootstrap, Bagging…. 00:18:00
scikit-learn – Decision Tree and Random Forests – Hands-on (Part 1) 00:19:00
scikit-learn – Decision Tree and Random Forests (Project Overview) 00:05:00
scikit-learn – Decision Tree and Random Forests (Project Solutions) 00:15:00
Python for Machine Learning - scikit-learn -Support Vector Machines (SVMs)
Support Vector Machines (SVMs) – (Theory Lecture) 00:07:00
scikit-learn – Support Vector Machines – Hands-on (SVMs) 00:30:00
scikit-learn – Support Vector Machines (Project 1 Overview) 00:07:00
scikit-learn – Support Vector Machines (Project 1 Solutions) 00:20:00
scikit-learn – Support Vector Machines (Optional Project 2 – Overview) 00:02:00
Python for Machine Learning - scikit-learn - K Means Clustering
Theory: K Means Clustering, Elbow method ….. 00:11:00
scikit-learn – K Means Clustering – Hands-on 00:23:00
scikit-learn – K Means Clustering (Project Overview) 00:07:00
scikit-learn – K Means Clustering (Project Solutions) 00:22:00
Python for Machine Learning - scikit-learn - Principal Component Analysis (PCA)
Theory: Principal Component Analysis (PCA) 00:09:00
scikit-learn – Principal Component Analysis (PCA) – Hands-on 00:22:00
scikit-learn – Principal Component Analysis (PCA) – (Project Overview) 00:02:00
scikit-learn – Principal Component Analysis (PCA) – (Project Solutions) 00:17:00
Recommender Systems with Python - (Additional Topic)
Theory: Recommender Systems their Types and Importance 00:06:00
Python for Recommender Systems – Hands-on (Part 1) 00:18:00
Python for Recommender Systems – – Hands-on (Part 2) 00:19:00
Python for Natural Language Processing (NLP) - NLTK - (Additional Topic)
Natural Language Processing (NLP) – (Theory Lecture) 00:13:00
NLTK – NLP-Challenges, Data Sources, Data Processing ….. 00:13:00
NLTK – Feature Engineering and Text Preprocessing in Natural Language Processing 00:19:00
NLTK – NLP – Tokenization, Text Normalization, Vectorization, BoW…. 00:19:00
NLTK – BoW, TF-IDF, Machine Learning, Training & Evaluation, Naive Bayes … 00:13:00
NLTK – NLP – Pipeline feature to assemble several steps for cross-validation… 00:09:00
Resources
Resources – Data Science and Machine Learning using Python : A Bootcamp 00:00:00

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Data Science and Machine Learning using Python : A Bootcamp

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