Duration: 8 Months, 2 Days and 6 Hours a Week
Student Exit profile: Machine Learning & Data Science Expert
Are you ready to start your path to becoming a Data Scientist!
This comprehensive course will be your guide to learning how to use the power of Python to analyze data, create beautiful visualizations, and use powerful machine learning algorithms!
Data Scientist has been ranked the number one job on Glass door and the average salary of a data scientist is over $120,000 in the United States according to Indeed! Data Science is a rewarding career that allows you to solve some of the world's most interesting problems!
Data scientist is one of the best suited professions to thrive this century. It is digital, programming-oriented, and analytical. Therefore, it comes as no surprise that the demand for data scientists has been surging in the job marketplace.
However, supply has been very limited. It is difficult to acquire the skills necessary to be hired as a data scientist.
Universities have been slow at creating specialized data science programs. (not to mention that the ones that exist are very expensive and time consuming)
Most courses in the market, focus on a specific topic and it is difficult to understand how the skill they teach fit in the complete picture.
This course is designed for both beginners with some programming experience or experienced developers looking to make the jump to Data Science!
We'll teach you how to program with Python, how to create amazing data visualizations, and how to use Machine Learning with Python!
Data Science bootcamps are costly, in thousands of dollars. However, this course is only a fraction of the cost of any such bootcamp and 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"!
In the course, you'll be learning the latest tools and technologies that are used by data scientists at Google, Amazon, or Netflix.
For your satisfaction, we 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
Arrays, built-in methods, array methods and attributes, indexing, slicing, broadcasting & Boolean masking, Arithmetic Operations & Universal Functions
Pandas Data Structures - Series, DataFrame, Hierarchical Indexing, Handling Missing Data, Data Wrangling - Combining, merging, joining, Group by, Other Useful Methods and Operations, Pandas Built-in Data Visualization
Basic Plotting & Object Oriented Approach
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:
Over fitting, under fitting Bias Variance Tradeoff
Confusion Matrix, True Negatives/Positives, False Negatives/Positives, Accuracy, Misclassification Rate / Error Rate, Specificity, Precision
K Nearest Neighbor
Curse of Dimensionality, Model Performance
Tree Depth, Splitting at Nodes, Entropy, Information Gain
Bootstrap, Bagging (Bootstrap Aggregation)
K Mean Clustering
Principle Component Analysis (PCA)
Support Vector Machine
Natural Language Processing (NLP)
Tokenization, Text Normalization, Vectorization, BoW, 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, transections 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.
Build Data Models and Recognition Projects:
Build a facial recognition project
Build a happy/sad face detection project
Build a simple digit recognition project using the MNIST handwritten digit database
Handwritten digit recognition with advanced MNIST
Build a simple linear regression model in PyCharm with TensorFlow
Build a simple image recognition project using the CIFAR-10 library
Image recognition with CIFAR-100
And much more!
Students of This Course Will Get Free:
Machine Learning & Data Science Kit
This kit will include:
Machine Learning & Data Science book that costs $100
Premium contents for Machine Learning & Data Science
And you'll also get access to this course's Facebook Group, where you can stay in touch with your classmates
Who this course is for:
For you, if you
Anyone interested in Machine Learning
Want to learn Data Science with Python
Want to learn Machine Learning with Python
Are tired of complicated courses and "Learn by Doing"
Students who have at least high school knowledge in math and who want to start learning Machine Learning
Any students in college who want to start a career in Data Science
Any data analysts who want to level up in Machine Learning
Any people who are not satisfied with their job and who want to become a Data Scientist
Any people who want to create added value to their business by using powerful Machine Learning tools
Software developers or programmers who want to transition into the lucrative data science and machine learning career path will learn a lot from this course
Technologists curious about how deep learning really works