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  • Grouping, Sorting, analysing, organizing, sorting, filtering, pivoting, aggregating and more!

  Hi?  Welcome to Python Data Science Essential Course for Data Analysis and Visualization. This course is essential for Python Programming Intermediate students with adequate Knowledge of Python. The learning content for this course is for Beginners in Data Science with a desire to further their knowledge by dive in into Data Science and Machine Learning, this is the right course for you. This course is easy to follow and teaches new concepts in  Data Analysis and Science.

In this course, we are going to cover, Data Structures and Binary Files followed by Pandas, Numpy, Random, Seaborn, SciPy and Matplotlib. With this course, you can start your journey in Data Science and Machine Learning. all that’s needed is your creativity and problem-solving skills. With this course, you can add confidence and programming skills competence to your resume. Data science is the field of study that combines domain expertise, programming skills, and knowledge of mathematics and statistics to extract meaningful insights from data.

Do not miss out on technology, these days everyone is a Data collector so, take your time with this course and learn how to manipulate data after collection. In Addition, if you are an expert with full and enough knowledge about Data Science this course is not for you and if you are in an advanced class already this course is not for you again. But if you are already a programmer and wish to learn Python Programming Language while specifically focusing on Data Science, then this course is definitely for you.

In this course, we will be using PyCharm and Anaconda .

  • Computer
  • Python Beginner level
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  • Section 1 : Course Introduction 4 Lectures 00:17:34

    • Lecture 1 :
    • What you will learn in this course Preview
    • Lecture 2 :
    • Installing PyCharm
    • Lecture 3 :
    • Anaconda Installation
    • Lecture 4 :
    • Anaconda Navigator Interface
  • Section 2 : PANDAS DATA ANALYSIS WITH PYTHON 8 Lectures 00:34:55

    • Lecture 1 :
    • Introduction lecture
    • Lecture 2 :
    • Pandas Data in series
    • Lecture 3 :
    • Dictionaries
    • Lecture 4 :
    • Dataframes
    • Lecture 5 :
    • Pandas dataframe
    • Lecture 6 :
    • Read CSV
    • Lecture 7 :
    • Analyzing Data
    • Lecture 8 :
    • Plotting with Pandas
  • Section 3 : Numeric Python Concept (NumPy) 14 Lectures 00:55:54

    • Lecture 1 :
    • Introduction Lecture
    • Lecture 2 :
    • Dimensional Arrays
    • Lecture 3 :
    • Indexing
    • Lecture 4 :
    • Slicing
    • Lecture 5 :
    • DataType
    • Lecture 6 :
    • Views
    • Lecture 7 :
    • Array Shape
    • Lecture 8 :
    • Array Convention
    • Lecture 9 :
    • Iteration
    • Lecture 10 :
    • Enumerated
    • Lecture 11 :
    • Joining
    • Lecture 12 :
    • Search
    • Lecture 13 :
    • Sort
    • Lecture 14 :
    • Filter
  • Section 4 : Random Python Concept 6 Lectures 00:25:05

    • Lecture 1 :
    • Introduction lecture
    • Lecture 2 :
    • Data Distribution
    • Lecture 3 :
    • Elements Permutation
    • Lecture 4 :
    • Visual Distribution
    • Lecture 5 :
    • Normal Graph
    • Lecture 6 :
    • Binomial Graph
  • Section 5 : Python Seaborn in Data Analysis 4 Lectures 00:26:46

    • Lecture 1 :
    • Data Structure
    • Lecture 2 :
    • Dataset
    • Lecture 3 :
    • Visualizing Data
    • Lecture 4 :
    • Color Concept
  • Section 6 : Python Matplotlib Tutorial 9 Lectures 00:35:43

    • Lecture 1 :
    • Introduction lecture
    • Lecture 2 :
    • Plotting
    • Lecture 3 :
    • Multiple Points Plotting
    • Lecture 4 :
    • Markers
    • Lecture 5 :
    • Line Construction Part 1
    • Lecture 6 :
    • Line Construction Part 2
    • Lecture 7 :
    • Label and Titles
    • Lecture 8 :
    • Subplots
    • Lecture 9 :
    • Pie Chart
  • Section 7 : Machine Learning Fundamentals 4 Lectures 00:25:03

    • Lecture 1 :
    • Section Overview
    • Lecture 2 :
    • Machine Learning Algorithm
    • Lecture 3 :
    • Getting Data for Machine Learning
    • Lecture 4 :
    • Statistical Attributes for Machine Learning
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My name is Fanuel Mapuwei. I am a professional Fullstack Python developer. I have more than 3+ years of experience in software development. I have developed several applications for savannah network company which helped them to simplify tasks. Fanuel Mapuwei is a Computer Science Graduate under the Guidance of the University of Zimbabwe.
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