A comprehensive course on Machine Learning using Python. This course is highly suited for beginners
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Introduction about data science and big data and its importance and will introduce about various programming languages (tools) used for data science.
Explanation about variables, operators, data types, data structure, control structure in Python, Function file in Python
Include Numpy, Scipy, Pandas, Matplotlib, Seaborn, etc.
This module will include basics of machine learning and its classification and include fitting of model with cross validation and bias variance trade off.
Evaluation metrics for model validation
EDA/ correlation/ feature extraction/ hyper parameters
This module will introduce univariate and multivariate linear regression and will explain how it can be implemented in Python
Explanation about Eigen values and Eigen vectors and singular value decomposition and then PCA
Explanation and implementation of logistic regression and k-nearest neighbor in Python
Explanation and implementation of Decision tree and Random forest in Python
Clustering of data using clustering algorithm
Explanation of logistic regression with neural network mindsets
Project 1
Highlights
“EarlySalary” a stock forecasting company has employed you as a Data Scientist. As a first job, the manager has provided you with stock market data and asked you to check the quality of data. There are two files “Stock_File_1.csv” and “Stock_File_2.txt”. Some details of the data shared with you are
(a) The data set consists of six variables namely-date, Open, High, Low, Close, Volume
(b) The stock market opens at 9:15 am and closes at 3:30 pm.
Each stock is defined by an opening price and closing price i.e. the price at which it open and the price at which it closes. During operating regime, the stock prices touches maximum and minimum price. You have an access to tens years of monthly stock price data with the open, high, low, close and the volume that signifies the number of stocks traded. On some day there is no trading, the open, high, low, close remains constant and the volume is zero. Now, you go to your manager after data visualization and exploratory analysis and model building (do not build a model, assume you built it for sake), your manager says the model predictions are poor as the data is polluted (reported by manager that that instant). Now try to impress your boss by doing some data preprocessing. Assume that you fill missing values by mean of the data corresponding to each feature. Remenber: please merge the data before preprocessing. You can use pandas.concat (read) to merge your data
Project 2
Highlights
“Sandman” is willing to do some manufacturing analytics for their manufacturing plant.
Description: The datasets consists of 13 variables and 388 samples. The table below gives the description of the data
SSandman corporation continuously looks to improve its manufacturing quality. Sandman monitors quality of input materials (physical and chemical properties) on a daily basis. Also, it monitors quality of output material for every batch and output rejection rates are available on daily basis. Sandman wishes to develop a early warning system (EWS) to predict likely rejection for the new day, given the input quality for that day. They hired you to develop EWS. Put all the knowledge gathered in the course to achieve your objective.
The software that will be used as a part of this course is Python and a compiler for Python, sublime text. Python finds widespread use in the industries, ranging from data analysis for simulations to automation where mundane tasks can be automated to save time.
This machine learning with python course opens up some fantastic opportunities for you in the best companies in India and abroad. You will learn concepts like data science, python programming, machine learning, linear regression, logistic regression, and neural network.
The introductory module deals with data science, the role of data scientists in the projection of future values, and the programming languages used. You will be introduced to variables, operators, data structure, and control structure as part of Python Programming. The course also includes the basics of machine learning, clustering of data using a clustering algorithm, Principal Component Analysis, Decision Tree, and Random Forest.
Concepts will be clarified through practical projects on data science and manufacturing analytics. As a data scientist, you will learn, for example, how to predict future stock market values using current data. Machine learning will help you develop early warning systems or EWS from given datasets.
You will get career openings in different industries such as machine learning engineers, Python programmers, Computer Vision Specialists, Natural Language Processing professionals, and Deep Learning professionals. The fees for this course range from Rs. 7,000/- to Rs. 15,000/- per month in India.
The machine learning with python course is meant for engineers. If you are an electrical engineer and want to pursue a career in machine learning and Artificial Intelligence, you will benefit from this course. Those who want to be part of AI or Artificial Intelligence-powered industries like e-commerce portals that use the technology to help customers choose products or movie channels should take this course.
You can enroll in this course if you have basic programming knowledge since it starts with entry-level machine learning concepts. It includes project work to help you learn the application of machine learning in diverse areas like google maps, fraud detection, customer segmentation, and more.
This machine learning course begins with an introduction to data science, why it is important, and the programming languages required.
Before starting the machine learning module, you will understand the essential Python libraries like Pandas, Numpy, Seaborn, Scipy, and more. Fitting of the model with cross-validation, bias-variance tradeoff, and the basics of machine learning will be taught in this course. Other essential components include K-Mean and Hierarchical Clustering, Logistic Regression and K-Nearest Neighbor, Principal Component Analysis, and more.
Multiple opportunities are available across different industry segments when you complete the machine learning with python course. Here are some of the top positions available:
1) Why should you enroll in this machine learning certification course?
The machine learning industry is growing at 44% a year, and there is a shortage of qualified professionals. There are highly-paid jobs for professionals who complete this course.
2) What will I learn in this course?
Some of the key topics covered in this course are the basics of programming, evaluation metrics, and essential python libraries.
3) What is the duration of the course?
The duration of the course is normally three months.
4)What are the benefits of this course?
This is the best machine learning certification course because it ensures high-paying positions in reputed companies. You will have the tools to provide meaningful insights for these companies from data using tools developed in Python.
5) What is the fee for this course?
The course fee ranges from Rs. 7,000/- to Rs. 15,000/- per month in India.
6) What are the top companies hiring machine learning engineers in India?
Top companies like Amazon, Facebook, Flipkart, and others need machine learners and similar professionals.
7) Who is eligible for this course?
This course is ideal for students with knowledge of statistics and programming. You should be eager to learn machine learning and look for a career in it.
8) How much salary can I expect after completing this course?
You can expect an average salary of Rs. 7.10 lacs to 7.94 lacs per annum.
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Any enthusiastic student with some knowledge of statistics and programming and who is willing to learn machine learning and build career in it.
Complete overview of the machine learning and its application
I am teaching Python, which is freeware and are most widely used in industries to solve machine learning problems.
Now a days, data is the fuel for everything. To extract meaningful insights from data, tools developed in Python will assist the participants to achieve this goal.
As there are almost too many companies that uses data science and machine learning to extract meaningful insight from data, therefore, it is very difficult to name such companies. Some of the field where data science and machine learning are used include hospital, pharma companies, manufacturing and process plants, etc.
If you are looking to do your MS or PhD in data science field, then absolutely this course is meant for you.
Since, data scientists, data engineer and data analyst are in demand in 20th century. There is huge scope that you will land up in high paying job after learning this course.
A dedicated 2 hours of time is more than enough to understand the concepts, noting the concepts down and performing the challenges.
Learn industry-relevant skills from technical experts
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Work on projects, publish to your profile and get hired in top companies
In the past 12 months, we have placed 200+ students, helped students get over USD 500,000 in scholarships
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