What will you learn in this course?

Our 12 sections in this course address every aspect of data science in a python programming language. This course will cover the following:

• Introduction to data science
• Introduction to python driven data science frameworks such as Anaconda.
• Interaction with python Jupyter notebooks
• Presentation of basic analytical tools- Numpy Arrays, Matrices, Vectors, Equation-solving, other Operations, Arithmetics, Broadcasting, and so on.
• Implementation of data science techniques
• The data structure of python
• Reading and analyzing data in Pandas such as JSON, HTML, CSV, Excel, files.
• Preprocessing and wrangling of data through various python techniques such as handling conditional data, NAS/No data or grouping attributes.
• Analyzing data through visualization techniques such as histograms, pie/line charts, scatterplots, barplots, boxplots, etc.
• Analysis, interference, and variables relationship through statistical data
• Supervised and unsupervised machine learning
• Artificial neural networks, deep learning discovery, and much more.

Why will this course offer you?

To acquire the key to the data science world through python.

The best part?

There is no pre-requisite to this course - neither machine learning nor statistics.

I will help you to get started with valuable concepts and techniques in python data science. As mentioned earlier, I have used the most simple, easy-to-understand, and straightforward methods to address every concept of python.

This course will be the proven ultimate guide for you that will help you to implement the data science and machine learning techniques in the real world. No matter, what type of data you want to analyze.

At the end of this course, you will be able to use python packages such as NumPy, matplotlib, and pandas in different scenarios. What is more?

Deep conceptualization of python's statistical modeling is not going anywhere if you invest your time in learning.

Even, I assure you that my course will cover other machine-related topics, too. For example, I have added lectures that cover deep learning along with neural networks incorporating multiple algorithms.

With this Powerful All-In-One Python Data Science course, you’ll know it all: visualization, stats, machine learning, data mining, and deep learning!

The underlying motivation for the course is to ensure you can apply Python based data science on real data and put into practice today. Start analyzing data for your own projects, whatever your skill level and IMPRESS your potential employers with actual examples of your data science abilities.

HERE IS WHAT THIS COURSE WILL DO FOR YOU:

This course is your one shot way of acquiring the knowledge of statistical data analysis skills that I acquired from the rigorous training received at two of the best universities in the world, perusal of numerous books and publishing statistically rich papers in renowned international journal like PLOS One

This course will:

(a) Take students without a prior Python and/or statistics background background from a basic level to performing some of the most common advanced data science techniques using the powerful Python based Jupyter notebooks.

(b) Equip students to use Python for performing different statistical data analysis and visualization tasks for data modelling.

(c) Introduce some of the most important statistical and machine learning concepts to students in a practical manner such that students can apply these concepts for practical data analysis and interpretation.

(d) Students will get a strong background in some of the most important data science techniques.

(e) Students will be able to decide which data science techniques are best suited to answer their research questions and applicable to their data and interpret the results.

It is a practical, hands-on course, i.e. we will spend some time dealing with some of the theoretical concepts related to data science. However, majority of the course will focus on implementing different techniques on real data and interpret the results. After each video you will learn a new concept or technique which you may apply to your own projects.