Machine Learning using Python Training & Certification

  • Course Duration75 Hrs.
  • Course ModeInstructor Led Training
  • Course Fee₹ 9100

About The Course

AICouncil certification and training program on Machine Learning is a well-planned program to master the technology as per recent trend and need. Participants will avail with real time data to work upon and develop algorithms using supervised, unsupervised, regression, classification, and time series modelling. You will see how python can be used for complex machine learning problems and get ready for challenging roles in the domain of Machine Learning and Artificial Intelligence.

Key Features

Instructor–led training

Highly interactive instructor-led training

Free lifetime access to recorded classes

Get lifetime access of all recored classes in your profile

Regular assignment and assessments

Real-time projects after every module

Lifetime accessibility

Lifetime access and free upgrade to the latest version

3 Years of technical support

Lifetime 24/7 technical support and query resolution

Globally Recognized Certification

Get global industry-recognized certifications

Highlights

  • How to use python for Machine Learning and Statistical Learning
  • Fundamentals of Machine Learning and Data Science
  • Optimization Techniques
  • Dimensionality reductions
  • Ensemble Learning
  • Neural Networks

Mode of Learning and Duration

  • Weekdays – 9 to 10 weeks
  • Weekend – 10 to 12 weeks
  • FastTrack – 7 to 8 weeks
  • Weekdays – 9 to 10 weeks
  • Weekend – 10 to 12 weeks
  • FastTrack – 7 to 8 weeks

 

Course Agenda

  • Define Data Science
  • Role of a Data Scientist
  • Life cycle of Data Science
  • Tools used in Data Science
  • Role of Big Data and Hadoop, Python, R and Machine Learning play in Data Science
  • What does Data Science involve?
  • Business Intelligence vs Data Science
  • Introduction to Python
  • Data Acquisition techniques
  • Different types of Data
  • Evaluate Input Data
  • Data Wrangling techniques
  • Data Exploration
  • Data Analysis Pipeline
  • Data Extraction
  • Raw and Processed Data
  • Visualization of Data
  • Hands-On: - Loading different types of dataset in Python
  • Hands-On: - Arranging the data
  • Hands-On: - Plotting the graphs
  • Need of Machine Learning
  • Introduction to Machine Learning
  • Types of Machine Learning, such as supervised, unsupervised and reinforcement learning
  • Why Machine Learning with Python and applications of Machine Learning
  • Introduction to supervised learning
  • Types of supervised learning - regression and classification
  • Introduction to regression
  • Simple linear regression
  • Multiple linear regression
  • Assumptions in linear regression, and math behind linear regression
  • Hands-on Exercise – Linear Regression and Train-Test Implementation
  • Importance of Dimensions
  • Why Dimensionality Reduction
  • PCA and its implementation
  • LDA and its implementation
  • Factor Analysis
  • Scaling dimensional model
  • Hands On: - PCA
  • Hands On: - Scaling
  • Introduction to classification
  • Linear regression vs logistic regression
  • Math behind logistic regression with detailed formulas
  • log it function and odds
  • Confusion matrix and accuracy
  • True positive rate v/s false positive rate
  • Threshold evaluation with ROCR
  • Hands-on Exercise – Logistic regression, Confusion matrix Implementation
  • Introduction to tree-based classification
  • Understanding a decision tree
  • Impurity function and entropy to understand the concept of information gain for the right split of node
  • Gini index
  • Overfitting
  • Pruning, pre-pruning, post-pruning, cost-complexity pruning
  • Introduction to ensemble techniques
  • Understanding bagging
  • Introduction to random forests
  • Finding the right number of trees in a random forest
  • Hands-on Exercise – Decision tree Implementation and hyper parameters in the random forest
  • Introduction to probabilistic classifiers
  • Understanding Naïve Bayes
  • Math behind the Bayes theorem
  • Understanding a support vector machine (SVM)
  • Kernel functions in SVM, and math behind SVM
  • Hands-on Exercise – Naïve Bayes and SVM implementation
  • Types of unsupervised learning
  • Clustering and dimensionality reduction
  • Types of clustering
  • Introduction to k-means clustering
  • Math behind k-means
  • Dimensionality reduction with PCA
  • Hands-on Exercise – K-Means and PCA implementation
  • Introduction to Natural Language Processing (NLP)
  • Introduction to text mining
  • Importance and applications of text mining
  • How NLP works with text mining
  • Writing and reading to word files
  • OS modules
  • Natural Language Toolkit (NLTK) environment and text mining: its cleaning, pre-processing and text classification
  • Hands-on Exercise – NLTK implementation
  • Define Association Rules
  • Backend of recommendation engines and develop your own using python
  • What are Association Rules?
  • Association Rule Parameters
  • Calculating Association Rule Parameters
  • Recommendation Engines
  • How Recommendation Engines work?
  • Collaborative Filtering
  • Content Based Filtering
  • Hands On: - Apriori Algorithm
  • Hands On: - Market Basket Analysis
  • Concept of Reinforcement Learning
  • Generalize a problem using Reinforcement Learning
  • Elements of Reinforcement Learning
  • Exploration vs Exploitation dilemma
  • Epsilon Greedy Algorithm
  • Markov Decision Process (MDP)
  • Q values and V values
  • Q – Learning
  • α values
  • Hands On: - Calculating Reward
  • Hands On: - Discounted Reward
  • Hands On: - Calculating Optimal quantities
  • Hands On: - Implementing Q Learning
  • Hands On: - Setting up an Optimal Action
  • Introduction to Deep Learning with neural networks
  • Biological neural network vs artificial neural network
  • Understanding perceptron learning algorithm
  • Introduction to Deep Learning frameworks
  • Tensor Flow constants
  • Variables and place-holders
  • Time series techniques and applications
  • Time series components
  • Moving average, smoothing techniques, exponential smoothing
  • Univariate time series models
  • Multivariate time series analysis
  • ARIMA model
  • Time series in Python
  • Sentiment analysis in Python (Twitter sentiment analysis)
  • Text analysis
  • Hands-on Exercise – Analysing and Forecasting using time series

 

Projects

Industry: - Real Estate

Problem Statement: -Predict Property Pricing using Linear Regression

With this project you will get hands-on experience with regression and optimization techniques like gradient descent to build a regression based model for property price prediction.

Industry: - Waste Management

Problem Statement: - Clssification of waste into two category, biodegradable and non-biodegradable using SVM.

Fate of a chemical in environment hugely depends upon its feature i.e. biodegradable or non-biodegradable. With different possible attributes you have to make a machime learningmodel which can classify the chemicals into two categories.

Industry: - FMCG and Super Market

Problem Statement: - Classify customers into different categories based upon their shopping habits.

With this project you can learn a lot about different machine learning algorithms with hands on experiences. The all you need to do is extracting meaningful insights out of data through manipulations and processings. Data visualization and algorithm implementations like linear regression, decision tree and Naive bayes will be done to get the classified output.

Industry: - Advertising

Problem Statement: -Make a targeted marketing campaigns for e-commerce platform

If you are trying to reach everyone, you can't reach anyone. Using the data of social interest of different people we can design very targeted marketing campaigns by implementing K-Means clustering into a segment of data.

Industry: - Banking

Problem Statement: -Make a predictive model to decide whether a person can avail loan or not

A bank try to develop a loan granting program for its consumer. Help the bank to develop such model using different machine Learning classification techniques to make predictions about the consumer at maximum accuracy that whether he/she will return the amount or not.

 


Certification

Career Support

We have a dedicated team which is taking care of our learners learning objectives.


FAQ

There is no such prerequisite if you are enrolling for Master’s Course as everything will start from scratch. Whether you are a working IT professional or a fresher you will find a course well planned and designed to incorporate trainee from various professional backgrounds.

AI Council offers 24/7 query resolution, you can raise a ticket with a dedicated support team and expect a revert within 24 Hrs. Email support can resolve all your query but if still it wasn’t resolved then we can schedule one-on-one session with our instructor or dedicated team. You can even contact our support after completing the training as well. There are no limits on number of tickets raised.
AI council provide two different modes for training one can choose for instructor lead training or learning with prerecorded video on demand. We also offer faculty development programs for college and schools. apart from this corporate training for organization/companies to enhance and update technical skills of the employees. We have highly qualified trainers who are working in the training industry from a very long time and have delivered the sessions and training for top colleges/schools and companies.
We are providing a 24/7 assistance for the ease of the student. Any query can be raised through the interface itself as well as can be communicated through email also. If someone is facing difficulties with above methods mentioned above we can arrange a one on one session with the trainer to help you with difficulties faced in learning. You can raise the query throughout the total training period as well as after the completion of the training.
AI Council offers you the latest, appropriate and most importantly the real-world projects throughout your training period. This makes student to gain industry level experience and converting the learning’s into solution to create the projects. Each Training Module is having Task or projects designed for the students so that you can evaluate your learning’s. You will be working on projects related to different industries such as marketing, e-commerce, automation, sales etc.
Yes, we do provide the job assistance so that a learner can apply for a job directly after the completion of the training. We have tied-ups with companies so when required we refers our students to those companies for interviews. Our team will help you to build a good resume and will trained you for your job interview.
After the successful completion of the training program and the submission of assignments/quiz, projects you have to secure at least B grade in qualifying exam, AI Council certified certificate will be awarded to you. Every certificate will be having a unique number through which same can be verified on our site.
To be very professional and transparent No, we don’t guarantee the job. the job assistance will help to provide you an opportunity to grab a dream job. The selection totally depends upon the performance of the candidate in the interview and the demand of the recruiter.
Our most of the programs are having both the modes of training i.e. instructor led and self-paced. One can choose any of the modes depending upon their work schedule. We provide flexibility to choose the type of training modes. While registering for courses you will be asked to submit your preference to select any of the modes. If any of the course is not offered in both modes so you can check in which mode, the training is going on and then you can register for the same. In any case if you feel you need any other training mode you can contact our team.
Yes, definitely you can opt for multiple courses at a time. We provide flexible timings. If you are having a desire for learning different topics while continuing with your daily hectic schedule our course timing and modes will help you a lot to carry on the learning’s.
Whenever you are enrolling in any of the courses we will send the notification you on your contact details. You will be provided with unique registration id and after successful enrollment all of the courses will be added to your account profile on our website.AI Council provides lifetime access to course content whenever needed.
A Capstone project is an outcome of the culminating learning throughout the academic years. It is the final project that represents your knowledge, efforts in the field of educational learning. It can be chosen by the mentor or by the students to come with a solution.
Yes, for obtaining the certificate of diploma programmer you have to submit the capstone project.