Data Management & Analytics

Data Management & Analytics

Special Gift (Additional Courses + Pdf Certificate + Transcript + Student ID) Worth £120 - Enrol Now!

Data is the new fuel of the 21st century powering several industries. One might even consider it as the new “black gold”. However, data is worthless until its transformation into invaluable insights, and that is data science.

Data Science is the process of mining massive quantities of structured and unstructured data to uncover hidden patterns and derive meaningful insights. It helps businesses easily comprehend large amounts of data and generate actionable insights to make more informed data-driven choices.

The significance of Data Science is in its many applications, which vary from simple tasks like asking Siri or Alexa for suggestions to more sophisticated ones like running a self-driving car. It is one of the most rapidly growing fields and sought-after career paths. If you also have a passion for finding solutions buried in data to address business issues, this Data Scientist Bundle course is for you.

This all-inclusive Data Management & Analytics course learning package will guide you through the ABCs of data science. You will equip yourself with numerous essential knowledge, such as — python essentials, data analysis using NumPy and Pandas, data visualisation using matplotlib, Pandas and Seaborn, etc. Additionally, this course will train you in interactive & geographical plotting using Plotly and Cufflinks.

To strengthen your knowledge basket, this course will also give you a comprehensive idea of machine learning. You will familiarise yourself with various machine learning models like Linear Regression Model, Logistic Regression Model, K Nearest Neighbors, etc.

Moreover, this course will tell you about the theory of Decision Tree and Random Forests. With this interactive data science training, you will clearly understand crucial topics like Support Vector Machines (SVMs), Principal Component Analysis (PCA), K Means Clustering, etc.

ThisBundle consists of the following Professional Career Oriented courses:

• Course 1: Data Science and Visualisation with Machine Learning
• Course 2: Python Course
• Course 3: SQL For Data Analytics & Database Development
• Course 4: Data Analysis, Automating and Visualisation in Excel

Add this Data Scientist Bundle to the basket — Develop the ability to extract valuable insights from gigabytes of data.

What skills you will gain:

• An extensive overview of data science.
• Complete understanding of python essentials.
• In-depth knowledge of data analysis using NumPy and Pandas.
• A good hold of data visualisation using matplotlib, Pandas and Seaborn.
• Dexterity in interactive & geographical plotting using Plotly and Cufflinks.
• Sharpened awareness of machine learning (ML)
• Comprehension of various machine learning models like Linear Regression Model, Logistic Regression Model, K Nearest Neighbors, etc.
• Proficiency in the theory of Decision Tree and Random Forests.
• Step-by-step guidance on Support Vector Machines (SVMs) and Principal Component Analysis (PCA).
• Expertise in K Means Clustering and Elbow method.

Should you have any questions while studying this course, our experienced tutors and mentors will answer them via email and live chat.

With our Student ID card you will get discounts on things like music, food, travel and clothes etc.

Enrol in our Data Management & Analytics today and start learning.

Why buy this course?

1. Unlimited access to all 4 courses for forever
2. Digital Certificate, Transcript and student ID all included in the price
3. Absolutely no hidden fees
4. Immediately receive the PDF certificate after passing
5. Receive the original copies of your certificate and transcript on the next working day
6. Easily learn the skills and knowledge from the comfort of your home
7. Get 3 additional courses included as bonus

Course Curriculum

Data Management & Analytics

**Data Science and Visualisation with Machine Learning**

Welcome, Course Introduction & overview, and Environment set-up

• Welcome & Course Overview
• Set-up the Environment for the Course (lecture 1)
• Set-up the Environment for the Course (lecture 2)
• Two other options to setup environment

Python Essentials

• Python data types Part 1
• Python Data Types Part 2
• Loops, List Comprehension, Functions, Lambda Expression, Map and Filter (Part 1)
• Loops, List Comprehension, Functions, Lambda Expression, Map and Filter (Part 2)
• Python Essentials Exercises Overview
• Python Essentials Exercises Solutions

Python for Data Analysis using NumPy

• What is Numpy? A brief introduction and installation instructions.
• NumPy arrays, built-in methods, array methods and attributes.
• Indexing, slicing, broadcasting & boolean masking
• Arithmetic Operations & Universal Functions
• NumPy Essentials Exercises Overview
• NumPy Essentials Exercises Solutions

Python for Data Analysis using Pandas

• What is pandas? A brief introduction and installation instructions.
• Pandas Introduction
• Pandas Data Structures – Series
• Pandas Data Structures – DataFrame
• Handling Missing Data
• Data Wrangling – Combining, merging, joining
• Groupby
• Useful Methods and Operations
• Project 1 (Overview) Customer Purchases Data
• Project 1 (Solutions) Customer Purchases Data
• Project 2 (Overview) Chicago Payroll Data
• Project 2 (Solutions Part 1) Chicago Payroll Data

Python for Data Visualization using matplotlib

• Matplotlib Essentials (Part 1) – Basic Plotting & Object Oriented Approach
• Matplotlib Essentials (Part 2) – Basic Plotting & Object Oriented Approach
• Matplotlib Essentials (Part 3) – Basic Plotting & Object Oriented Approach
• Matplotlib Essentials – Exercises Overview
• Matplotlib Essentials – Exercises Solutions

Python for Data Visualization using Seaborn

• Introduction & Installation
• Distribution Plots
• Categorical Plots (Part 1)
• Categorical Plots (Part 2)
• Axis Grids
• Matrix Plots
• Regression Plots
• Controlling Figure Aesthetics
• Exercises Overview
• Exercise Solutions

Python for Data Visualization using pandas

• Pandas Built-in Data Visualization
• Pandas Data Visualization Exercises Overview
• Panda Data Visualization Exercises Solutions

Python for interactive & geographical plotting using Plotly and Cufflinks

• Interactive & Geographical Plotting (Part 1)
• Interactive & Geographical Plotting (Part 2)
• Interactive & Geographical Plotting Exercises (Overview)
• Interactive & Geographical Plotting Exercises (Solutions)

Capstone Project - Python for Data Analysis & Visualization

• Project 1 – Oil vs Banks Stock Price during recession (Overview)
• Project 1 – Oil vs Banks Stock Price during recession (Solutions Part 1)
• Project 1 – Oil vs Banks Stock Price during recession (Solutions Part 2)
• Project 1 – Oil vs Banks Stock Price during recession (Solutions Part 3)
• Project 2 (Optional) – Emergency Calls from Montgomery County, PA (Overview)

Python for Machine Learning (ML) - scikit-learn - Linear Regression Model

• Introduction to ML – What, Why and Types…..
• Theory Lecture on Linear Regression Model, No Free Lunch, Bias Variance Tradeoff
• Linear Regression Model – Hands-on (Part 1)
• Linear Regression Model Hands-on (Part 2)
• Good to know! How to save and load your trained Machine Learning Model!
• Linear Regression Model (Insurance Data Project Overview)
• Linear Regression Model (Insurance Data Project Solutions)

Python for Machine Learning - scikit-learn - Logistic Regression Model

• Theory: Logistic Regression, conf. mat., TP, TN, Accuracy, Specificity…etc.
• Hands-on (Part 1)
• Hands-on (Part 2)
• Hands-on (Part 3)
• Hands-on (Project Overview)
• Hands-on (Project Solutions)

Python for Machine Learning - scikit-learn - K Nearest Neighbors

• Theory: K Nearest Neighbors, Curse of dimensionality ….
• K Nearest Neighbors – Hands-on
• scikt-learn – K Nearest Neighbors (Project Overview)
• K Nearest Neighbors (Project Solutions)

Python for Machine Learning - scikit-learn - Decision Tree and Random Forests

• Theory: D-Tree & Random Forests, splitting, Entropy, IG, Bootstrap, Bagging….
• Hands-on (Part 1)
• (Project Overview)
• (Project Solutions)

Python for Machine Learning - scikit-learn -Support Vector Machines (SVMs)

• Support Vector Machines (SVMs) – (Theory Lecture)
• Support Vector Machines – Hands-on (SVMs)
• Support Vector Machines (Project 1 Overview)
• Support Vector Machines (Project 1 Solutions)
• Support Vector Machines (Optional Project 2 – Overview)

Python for Machine Learning - scikit-learn - K Means Clustering

• Theory: K Means Clustering, Elbow method …..
• K Means Clustering – Hands-on
• K Means Clustering (Project Overview)
• K Means Clustering (Project Solutions)

Python for Machine Learning - scikit-learn - Principal Component Analysis (PCA)

• Theory: Principal Component Analysis (PCA)
• Principal Component Analysis (PCA) – Hands-on
• Principal Component Analysis (PCA) – (Project Overview)
• Principal Component Analysis (PCA) – (Project Solutions)

Recommender Systems with Python - (Additional Topic)

• Theory: Recommender Systems their Types and Importance
• Python for Recommender Systems – Hands-on (Part 1)
• Python for Recommender Systems – – Hands-on (Part 2)

Python for Natural Language Processing (NLP) - NLTK - (Additional Topic)

• Natural Language Processing (NLP) – (Theory Lecture)
• NLTK – NLP-Challenges, Data Sources, Data Processing …..
• NLTK – Feature Engineering and Text Preprocessing in Natural Language Processing
• NLTK – NLP – Tokenization, Text Normalization, Vectorization, BoW….
• NLTK – BoW, TF-IDF, Machine Learning, Training & Evaluation, Naive Bayes …
• NLTK – NLP – Pipeline feature to assemble several steps for cross-validation…

Certification

After studying the course materials you will be able to take the MCQ test that will assess your knowledge. After successfully passing the test you will be able to claim the pdf certificate for free. Original Hard Copy certificates need to be ordered at an additional cost of £8.

This course does not require you to have any prior qualifications or experience. You can just enrol and start learning.

This Data Management & Analytics was made by professionals and it is compatible with all PC’s, Mac’s, tablets and smartphones. You will be able to access the course from anywhere at any time as long as you have a good enough internet connection.

Following completion of this Data Science course, you will have a plethora of employment opportunities, including —

• Data Scientist.
• Data Architect.
• Data Analyst.
• Data Engineer.
• Machine Learning Engineer.

In the United Kingdom, these occupations are compensated between £25,000 and £85,000 per year.

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