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The Complete Data Science and Machine Learning using Python

Online Course. Data Science and Machine Learning are the hottest skills in demand but challenging to learn. Did you wish that there was one course for Data Science that covers everything from Math, Advance Statistics, Data Processing, Machine Learning, Deep learning and more?

What you’ll learn

  • Learn Complete Data Science skillset required to be a Data Scientist with all the advance concepts
  • Master Python Programming from Basics to advance as required for Data Science and Machine Learning
  • Learn complete Mathematics of Linear Algebra, Calculus, Vectors, Matrices for Data Science and Machine Learning.
  • Become an expert in Statistics including Descriptive and Inferential Statistics.
  • Learn how to analyse the data using data visualization with all the necessary charts and plots
  • Perform data Processing using Pandas and ScikitLearn
  • Master Regression with all its parameters and assumptions
  • Solve a Kaggle project and see how to achieve top 1 percentile
  • Learn various classification algorithms such as Logistic Regression, Decision Tree, Random Forest, Support Vector Machines
  • Get complete understanding of deep learning using Keras and Tensorflow
  • Become the Pro by learning Feature Selection and Dimensionality Reduction

Requirements

  • No prerequisites. I will teach right from basics in Python to Advanced Deep Learning
  • Passion to deal with data analysis

Description

Data Science and Machine Learning are the hottest skills in demand but challenging to learn. Did you wish that there was one course for Data Science that covers everything from Math, Advance Statistics, Data Processing, Machine Learning, Deep learning and more?

Well, you have come to the right place. This course has 240+ lectures, more than 24+ hours of content11 projects including one Kaggle competition with top 1 percentile score, code templates and various quizzes.

Today Data Science and Machine Learning is used in almost all the industries, including automobile, banking, healthcare, media, telecom and others.

As a data scientist, you will have to research and look beyond normal problems, you may need to do extensive data processing. experiment with the data using advance tools and build amazing solutions for business. However, where and how are you going to learn these skills? Do we even know what skills are required to be a successful Data Scientist?

Data Science and Machine Learning require in-depth knowledge of various topics. It is not just about knowing certain packages/libraries and learning how to apply them. Data Science requires an indepth understanding of the following skills,

  • Understanding of the overall landscape of Data Science and Machine Learning
  • Different types of Analytics, Architecture, Deployment characteristics of Data Science and Machine Learning projects
  • Programming skills preferably using the most popular language of Python
  • Mathematics including Linear Algebra, Calculus and how it is applied in Machine Learning Algorithms as well as Data Science
  • Statistics and Statistical Analysis for Data Science
  • Data Visualization
  • Data processing and manipulation
  • Machine Learning
  • Ridge (L2), Lasso (L1) and Elasticnet Regression/Regularization
  • Feature Selection and Dimensionality Reduction
  • Cross Validation for Model Selection
  • Cluster Analysis
  • Deep Learning using most popular tools and technologies of today.

This course has been designed considering all of the above aspects. In many courses, algorithms are taught without teaching Python or such programming language. However, it is very important to understand the construct of the language in order to implement any discipline leave alone Data Science and Machine Learning.

Also, without understanding the Mathematics and Statistics it’s impossible to understand how some of the Data Science and Machine Learning algorithms and techniques work.

Data Science and Machine Learning is a complex set of topics which are interlinked. However, we firmly believe in what Einstein once said,

“If you can not explain it simply, you have not understood it enough.”

As an instructor, I always try my level best to live up to this principle. This is one comprehensive course that teaches you everything required to learn Data Science and Machine Learning using the simplest examples with great depth.

As you will see from the preview lectures, some of the most complex topics are explained in a simple language.

Some of the key skills you will learn,

  • Python Programming Python has been ranked as the #1 language for Data Science and Machine Learning. It is easy to use and is rich with various libraries and functions required for performing various data processing tasks. Moreover, it is the most preferred and default language of use for many frameworks including Tensorflow and Keras.
  • Advance Mathematics Mathematics is the very basis for Data Science in general and Machine Learning in particular. Without understanding the meanings of Vectors, Matrices, their operations as well as understanding Calculus, it is not possible to understand the foundation of the Machine Learning. Gradient Descent which forms the very basis of Neural Network loss computation is built upon the basics of Calculus and Derivatives.
  • Advance Statistics It is not enough to know only mean, median, mode etc. The advance techniques of Data Science such as Feature Selection, Dimensionality Reduction using PCA are all based on advance inferential statistics of Distributions and Statistical Significance. It also helps us understanding the data behavior and then apply an appropriate technique to get the best result.
  • Data Visualization As they say, picture is worth a thousand words. Data Visualization is one of the key techniques of Data Science used for Exploratory Data Analysis. In that, we visually analyse the data to identify the patterns and trends. We are going to learn how to create various plots and charts as well as how to analyse them for all the practical purposes.
  • Data Processing Data Scientists spend more than 2/3rd of the time processing and analysing the data. Data can be noisy and is never in the best shape and form. Data Processing is one of the key disciplines of Data Science and Machine Learning to get the best results. We will be using Pandas which is the most popular library for data processing in Python and various other libraries to read, analyse, process and clean the data.
  • Machine Learning The heart and soul of Data Science is the predictive ability provided by the algorithms from Machine Learning and Deep Learning. This takes the overall discipline of Data Science ahead of others. We will combine everything we would learn from the previous sections and build various machine learning models. The key aspects of the Machine Learning is not just about the algorithms but also understanding various parameters. We will understand all the key parameters and how their values impact the outcome so that you can build the best machine learning models.
  • Feature Selection and Dimensionality Reduction In case you wonder, what makes a good data scientists, then this section is the answer. A good data scientist does not just use libraries and code few lines. She will analyse every feature of the data objectively and choose the most relevant ones based on statistical analysis. We will learn how to reduce the number of features as well as how we can retain the value in the data when we practice and build various machine learning models after applying the principles of Feature Selection and Dimensionality Reduction using PCA.
  • Deep Learning You can not become a good data scientist, if you do not know how to build a powerful neural network. We are going to learn some key fundamentals of Deep Learning and build a solid foundation first. We then will then use Keras and Tensorflow which are the most popular Deep Learning frameworks in the world.
  • Kaggle Project As an aspiring Data Scientists, we always wish to work on Kaggle project and achieve good results. I have spent huge effort and time in making sure you understand the overall process of performing a real Data Science and Machine Learning project. This is going to be a good challenge for you.

Your takeaway from this course,

  1. Complete hands-on experience with huge number of projects and exercises
  2. Learn the advance techniques used in the Data Science
  3. Certificate of Completion
  4. All the queries answered in shortest possible time.
  5. All future updates based on updates to libraries, packages
  6. Continuous enhancements and addition of future course material
  7. All the knowledge at fraction of cost

This course comes with the Udemy’s 30-Day-Money-Back Guarantee with no questions asked.

So what you are waiting for? Hit the “Buy Now” button and get started on your Data Science and Machine Learning journey without spending much time.

I am so eager to see you inside the course.

Disclaimer: All the images used in this course are either created or purchased/downloaded under the license from the provider. Majority of the images are from Shutterstock or Pixabay.Who this course is for:

  • Beginners as well as advance programmers who want to make a career in Data Science and Machine Learning

See more Data Science Online Courses


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