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Data Science and Machine Learning using Python – A Bootcamp – Udemy

(10 customer reviews)

$15

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Description

What you’ll learn

  • Python to analyze data, create state of the art visualization and use of machine learning algorithms to facilitate decision making.
  • Python for Data Science and Machine Learning
  • NumPy for Numerical Data
  • Pandas for Data Analysis
  • Plotting with Matplotlib
  • Statistical Plots with Seaborn
  • Interactive dynamic visualizations of data using Plotly
  • SciKit-Learn for Machine Learning
  • K-Mean Clustering, Logistic Regression, Linear Regression
  • Random Forest and Decision Trees
  • Principal Component Analysis (PCA)
  • Support Vector Machines
  • Recommender Systems
  • Natural Language Processing and Spam Filters
  • and much more……………….!

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Greetings, 

I am so excited to learn that you have started your path to becoming a Data Scientist  with my course. Data Scientist is in-demand and most satisfying career, where you will solve the most interesting problems and challenges in the world. Not only, you will earn average salary of over $100,000 p.a., you will also see the impact of your work around your, is not is amazing?

This is one of the most comprehensive course on any e-learning platform (including Udemy marketplace) which uses the power of Python to learn exploratory data analysis and machine learning algorithms. You will learn the skills to dive deep into the data and present solid conclusions for decision making. 

Data Science Bootcamps are costly, in thousands of dollars. However, this course is only a fraction of the cost of any such Bootcamp and includes HD lectures along with  detailed code notebooks for every lecture. The course also includes practice exercises on real data for each topic you cover, because the goal is “Learn by Doing”! 

For your satisfaction, I would like to mention few topics that we will be learning in this course:

  • Basis Python programming for Data Science

  • Data Types, Comparisons Operators, if, else, elif statement, Loops, List Comprehension, Functions, Lambda Expression, Map and Filter

  • NumPy

  • Arrays, built-in methods, array methods and attributes, Indexing, slicing, broadcasting & boolean masking, Arithmetic Operations & Universal Functions

  • Pandas

  • Pandas Data Structures – Series, DataFrame, Hierarchical Indexing, Handling Missing Data, Data Wrangling – Combining, merging, joining, Groupby, Other Useful Methods and Operations, Pandas Built-in Data Visualization

  • Matplotlib

  • Basic Plotting & Object Oriented Approach

  • Seaborn

  • Distribution & Categorical Plots, Axis Grids, Matrix Plots, Regression Plots, Controlling Figure Aesthetics

  • Plotly and Cufflinks

  • Interactive & Geographical plotting

  • SciKit-Learn (one of the world’s best machine learning Python library) including:

  • Liner Regression

  • Over fitting , Under fitting Bias Variance Trade-off, saving and loading your trained Machine Learning Models

  • Logistic Regression

  • Confusion Matrix, True Negatives/Positives, False Negatives/Positives, Accuracy, Misclassification Rate / Error Rate, Specificity, Precision

  • K Nearest Neighbour (KNN)

  • Curse of Dimensionality, Model Performance

  • Decision Trees

  • Tree Depth, Splitting at Nodes, Entropy, Information Gain 

  • Random Forests

  • Bootstrap, Bagging (Bootstrap Aggregation)

  • K Mean Clustering

  • Elbow Method 

  • Principle Component Analysis (PCA)

  • Support Vector Machine

  • Recommender Systems

  • Natural Language Processing (NLP)

  • Tokenization, Text Normalization, Vectorization, Bag-of-Words (BoW), Term Frequency-Inverse Document Frequency (TF-IDF), Pipeline feature……..and MUCH MORE……….!

Not only the hands-on practice using tens of real data project, theory lectures are also provided to make you understand the working principle behind the Machine Learning models.

So, what are you waiting for, this is your opportunity to learn the real Data Science with a fraction of the cost of any of your undergraduate course…..!

Brief overview of Data around us:

According to IBM, we create 2.5 Quintillion bytes of data daily and 90% of the existing data in the world today, has been created in the last two years alone. Social media, transactions records, cell phones, GPS, emails, research, medical records and much more…., the data comes from everywhere which has created a big talent gap and the industry, across the globe, is experiencing shortage of experts who can answer and resolve the challenges associated with the data. Professionals are needed in the field of Data Science who are capable of handling and presenting the insights of the data to facilitate decision making. This is the time to get into this field with the knowledge and in-depth skills of data analysis and presentation.

Have Fun and Good Luck! 

Who this course is for:

  • For you, if you:
  • want to learn Data Science with Python
  • want to learn Machine Learning with Python
  • are tired of complicated courses and “Learn by Doing”

Course content

  • Welcome, Course Introduction & overview, and Environment set-up
  • Python Essentials
  • Python for Data Analysis using NumPy
  • Python for Data Analysis using Pandas
  • Python for Data Visualization using matplotlib
  • Python for Data Visualization using Seaborn
  • Python for Data Visualization using pandas
  • Python for interactive & geographical plotting using Plotly and Cufflinks
  • Capstone Project – Python for Data Analysis & Visualization
  • Python for Machine Learning (ML) – scikit-learn – Linear Regression Model

10 reviews for Data Science and Machine Learning using Python – A Bootcamp – Udemy

  1. Donny Phan

    Super practical. Lessons are catered towards anyone looking to find work in this industry. It felt very comprehensive and gave me a broad understanding of the programming spectrum

  2. Madhav raj Verma

    Thanks for your great effort. i am fully satisfied with this course the way you teach and your explanation are very clear ,The content you provide in your course no one can do this at this price.

  3. Sachin Gupta

    I really didn’t want to leave a low rating as Angela is a great teacher. The 1st half of this course was terrific. The 2nd half was terrible. Under the justification of “teaching students how to figure things out on their own”, pretty much all videos and all explanations were dropped. You were just told what to do, given links to documentation and told to figure it out on your own. I understand doing that to some degree, but to revert to that entirely for nearly half the content barely makes this a course. It’s just a list of things for you to learn, then you’re left on your own to learn them. The 2nd half was so bad, especially the data science component, that I didn’t bother finishing the course.

  4. Vincent Beaudet

    Amazing 40 days course.
    Angela is a great teacher.
    The other 60 days are all about web developement, interacting with web pages, on your own with little to no explanations. I did not expect that at all. I wanted to learn more about software and scripting.
    This left me disappointed , confused and i started to doubt myself. Not a fun experience after the amount of effort i’v put in this course.

    Exercices format and explanations for the first 40 days were worth it tho.

  5. Ben K

    Not just an introduction to python, but really helps you learn fundamental aspects of python and coding in general. Some parts may require some knowledge on the subject (data science comes to mind) and there is quite some web development in the course. So, a few areas were not completely to my liking (I would have liked to see it done differently), but this course deserves the 5 stars in my opinion.

  6. Omid Alikhel

    I found the method a bit difficult when a code is written and then changed back to something different, with no enough explanation of how something happened and where it came from or a step by step explanation of why something is happening, i have no doubt in the instructors talent, but we are beginners!

  7. Devang Jain

    The course is not updated and most of the solution codes don’t work and there are no video solutions towards the end

  8. Szymon Kozak

    I think that the course tutor is really good in giving right information to learn at the right time. Thanks to this fact, my understanding of coding in python after 29 days of learning is above my expectations.

  9. Begoña Ruiz Diaz

    Ha sido la mejor elección que podría haber hecho.

  10. Vaibhav Sachdeva

    I want to thank Angela for making such an amazing course. It really helped me explore more things with python.

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