Python Machine Learning and Deep Learning

urther solidify your learning. Lifetime access to recorded training session videos, so learning stays with you. In-depth learning and practicals of Supervised & Unsupervised Learning. Once you finish this course you would have taken a giant leap towards the future of data analysis. Live Online Training For 6 Weekends
Extensive Practical Exercises Every Week​​​​
Access To Recorded Training
Sessions Life Time

WHO CAN ATTEND? Developers

Developers of Java, .Net, Javascript, Mainframes, Hadoop, Scala, Swift or any other programming language can learn Python from Scratch and also master Machine Learning with practical hands-on exercises to increase job prospects many fold. Business/Data Analysts

Business and System Analyst professionals can take advantage of this course by acquiring hands-on knowledge of Python as well as Machine Learning to successfully take up Data Science and Machine Learning projects. This course provides a great chance to transform your testing career by acquiring sought-after skill set .i.e. Python and Machine Learning. Project Leads/Managers

Professional leading IT teams as Project Lead and Project Managers will benefit by investing in new technologies like Python and Machine Learning to enhance their technical skill set and get a chance to lead and work with Python & machine Learning teams. BI & Data Visualisation Prof. This Course is extremely beneficial for BI and Data Visualisation professionals who are working on tools like Tableau Qlikview, FusionCharts, Highcharts, Datawrapper, Plotly, Sisense, Dundas, IntelliFront BI, Domo, Style Intelligence, Looker. Students

Fresh BE/B. TECH/MCA/BCA/ B Sc. IT graduates will gain competitive edge by learning Python and Machine Learning at the very start of their career. It will give them immense benefits over other fresh graduates in today’s competitive Job Market. COURSE CURRICULUM

Module 1 : Python

WEEK : 1

Module 1: Introduction

What is their expectation from course? Module 1.1 Python Basics

Python history
Development environment setup
First python program
Keywords, Statements, Data types, Operators
Exercise 1
Module 1.2 Python Flow Control

If else, For loop, While loop
Exercise 2
WEEK : 2

Module 1.3 Python Functions

Functions, Argument, Modules, Packages
Exercise 3
Module 1.4 Native Data Types

Numbers, List, Tuples, Strings, Sets, Dict. Exercise 4
WEEK : 3

Module 1.5 File Handling

File operations, File Directory, Exceptions
Exercise 5
Module 1.6 Scientific Python Packeges

Numpy, Pandas, Matplotlib, sciklit-learn
Exercise 6
Module 2 : Machine Learning

WEEK : 4

Module 2.1: Introduction

What is Machine Learning
Common use of machine learning (spam, house price,stock price-6 examples)
Different machine learning techniques

Module 2.2 Supervised Learning

What is supervised learning? Regression vs Classification

Module 2.2.1 Linear Regression

What is linear regression? Case Study
Model Tuning
Predictions
WEEK : 5

Module 2.2.2 Regularization

What is Regularization? LASSO Regression
Ridge Regression
Module 2.2.3 Logistic Regression

What is logistic regression? Case study
Model Tuning
Predictions
Module 2.2.4 Decision Trees & K-Nearest Neighbors

What is Decision Trees? Case study
Model Tuning
Predictions
WEEK : 6

Module 2.3 Unsupervised Learning

What is Unsupervised Learning? Different Unsupervised Algorithms? K-Means Clustering
Principal Component Analysis
Linear Discriminant Analysis
Module 2.3.1 K-means Clustering

What is K-means Clustering
Case Study
Model Tuning
Predictions
Conclusion

Summary
Next Steps

1. What is Machine Learning? Traditional programs take data as input and produces data as output. However a machine learning algorithm takes data as input but produces a program as an output. This machine generated program can now take new data, process it and produce output data. Machine learning algorithms automate the process of creating programs using historical data. In simple words, it gives computers the capability to extract knowledge from data and store it for future judgement. Wikipedia defines machine learning as…
"Machine learning is the subfield of computer science that, according to Arthur Samuel, gives “computers the ability to learn without being explicitly programmed”.


2. I am not a programmer, can I enroll in this course? Yes you can. Our course doesn't require a prior knowledge of Python programming. We devote the first few sessions in giving an in depth and hands on understanding of Python. In fact most of our students don't know Python before they join our course. This course is ideal for students who do not have any programming experience. There are very few courses that teach machine learning from scratch. We are proud to be one of the few training courses that teach machine learning from scratch.


3. I do not know Python, will you teach Python too in the program? Our course will take you from zero to machine learning hero in 42 days. It is designed in such a way that you don't need to know any programming language before joining this course. We divide the training in two parts. In the first part we teach Python with detailed classroom sessions, hand on exercises, sharing our simple and easy to follow handouts, home assignments and lots of videos from our previous classes. Once you complete our instructor led classroom course you will become a pro in Python, machine learning and data science.


4. How to learn Machine Learning using Python? Performing machine learning using Python is the best choice. Python programming language is designed for data analysis. It is the language of choice for data scientists around the world. Machine learning using python should be done in two steps. In first step one should pay attention to learning relevant Python skills that power you with good data handling and manipulation skills. In the second step, one should pick up the scikit-learn library and start using its data sets and algorithms to practice machine learning. We recommend that you install Anaconda distribution as it will get you Python, scikit-learn and many other data science libraries on your computer in easy one step installation. Our instructor led online classroom course specializes in teaching students cutting edge machine learning algorithms using Python. For more questions you can email us at [email protected]


5. What machine do I require to set up the Python on my Laptop/Desktop? Python programming language is cross platform. Its an interpreted language and its community has built interpreters for all the popular operating systems. We have trained students in Machine learning with different operating systems like Windows, Mac, Linux, Ubuntu etc. If your machine has 4GB of RAM and a free space of 0.5 GB on your hard disk, you are good to go. One more thing we recommend is a Mic. You will use it to interact with the instructor during the live classroom sessions. However if you don't have a mic, you can still attend the course and use the chat feature of our online classroom.


6. Will I get assistance to set up and Install Python before training starts? Before the training starts we send out a detailed step by step guide on what to do before your first class. Our handbook will give all the links, resources and guide necessary to install the relevant software on all the popular operating systems. It takes about 15 minutes to go through the instructions and make the necessary installations before the class starts. Sometimes students face issues installing and we help them get over their issue. In short you will not have any issue in getting setup before the training starts.


7. How easy is it to learn Python to implement Machine Learning? Python is one of the Top 3 programming languages of the world. The main reason for it to hold this spot is its simplicity and ease of use. If there is any programming language that somebody wants to pick for understanding software, Python is a good choice. It is simple, data friendly and last but not the least open source. In our machine learning course students join from all over the world who don't have any programming knowledge. We help them become ready to code in Python in 2-3 weeks as part of our machine learning course.