JOIN FREE INFORMATION SESSION ON

MACHINE LEARNING AND ARTIFICIAL INTELLIGENCE

Date : 1st December 2019

Time: From 11 AM till 1PM

Venue: 6th Floor, Akruti Trade Center, 91 Springboard, MIDC, Andheri East, Mumbai 400097

AGENDA

Know about aCubeIT ‘s ML-AI Training program.

Understand the complexity of ML-AI Learning curve.

Why its important to upgrade your skill set ?

Why there is rapid adoption of ML-AI in the Industry ?

How ML-AI can provide you a better career opportunity ?

This is a Instructor led classroom session

KEY HIGHLIGHTS OF OUR TRAINING PROGRAM

  • Small batches not exceeding 10 students per batch
  • 100% of Instructors are ML-AI Practitioners
  • One on One mentorship on project work
  • Mentorship for Entrepreneur students
  • Career guidance and coaching
  • Target the best Industry jobs

30%
Teaching

50%
Hands-on

20%
Mentoring

What will you get?

  • High quality learning experience
  • Team of Data Scientists as Teaching assistants
  • Personal attention

What will you learn?

  • High level research capability to find innovative solutions to complex business problems
  • Apply researched ideas to solve real life business problems
  • Experience of working on Real Data sets

Fundamentals of ML and Programming in Python

Introduction to Python for Data Science

Exploratory Data Analysis

Data Munging

Machine Learning Models

Developing Machine Learning applications

Note: Detailed Course topics are mentioned in FAQ section below.

 

Eligibility:

This training program is primarily for professionals with IT or Non IT background seeking formal qualifications in Data Science, Machine Learning and Artificial Intelligence.

People working in the field of Banking and Finance, Information and Technology, Retail, Healthcare, Biotechnology, Automobile, Media and Entertainment etc can join the course.

BE/B.Tech: Any stream/Graduates in Maths, Statistics, Pharma, Social Sciences, Economics can get best out of it. 

Our program covers most of the programming fundamentals that are required to be a good data scientist.

Prerequisites:

Students should know school level Mathematics.

They must a carry a laptop. 8GB RAM / Linux is preferable.

 

Duration: 5 Months Instructor led Weekend Classes.

Classes will be conducted one day (either on Saturday or Sunday) for 4 hours every week. Timing is 10 AM to 2 PM. 

Students can talk/visit/meet their teachers/Assistants for any help,  during the week-days with prior appointments. 

Weekly Assignments should be completed and submitted every week.

A Capstone project will be started by the end of 3rd month.

Class room location: 6th Floor, Akruti trade center, 91 Springboard, MIDC, Andheri East, Mumbai: 400093

All the instructors are Machine Learning and AI practitioners. All of them have exposure of working on overseas ML-AI Consulting and high level research projects. 

We teach python from basics, so no prior experience in python is required.

Programing experience is desirable but its not mandatory. We had few students who were graduate in statistics with no programing experience. They joined our courses and today they are working as data scientists in MNC companies. You need to work hard to pick up the programing fundamentals that will help you in excelling in your career. 

Our training program is focussed on transforming students as a great data scientist. Data scientist jobs are most trending jobs today. Its very high in demand. 

You will be trained to extract massive amount of data and analyze it to find key insights/patterns in the data. You will learn to apply various kinds of ML algorithms to predict future events. For eg: A Data scientist will analyze the past purchase behaviour of millions of  customers on a eCommerce web site and build a ML model to predict how many of the customers are going to do their next purchase in what time frame ( next week, next month etc).

The job of a data engineer is to deploy the ML model on a eCommerce platform, do various kind of application/data/API integrations etc. Data Engineering jobs are more of programing /coding while Data scientist job is focused towards research, analytical work.

We have a given a very high level detail of the topics. Detail of the topics are mentioned here.

üModule 1A: Fundamentals of ML and Programming in Python
üFundamentals of ML
üWhat is machine learning?
üTypes of learning: Supervised, Unsupervised & semi-supervised
üMachine Learning Goals & Objectives: Clustering, Classification, Regression, Anomaly Detection, Recommendation Engines
üMachine Learning Algorithms Overview:
üSupervised Regression: Simple & Multiple Regression, Decision Tree & Forest Regression, Artificial Neural Networks, Nearest Neighbor Methods
üSupervised Two-Class & Multi-Class Classification: Logistic and multinomial regression, Artificial Neural Networks, Decision Tree & Forest Classification, SVM (Support Vector Machine), Nearest Neighbor, Methods, one-versus-all multiclass
üUnsupervised: K-means & Hierarchical Clustering
üEnsemble Models
üUnderstanding High Bias & High Variance, Bias-Variance Trade-off
üData Requirements for Machine Learning
üData Selection & Preprocessing, Selection Bias, Missing Data, Outliers, Feature Scaling, Dummy variables, Feature Selection & Feature Engineering, Model Selection, Model Trade-offs, Overfitting, Controlling Model Complexity, Regularization, Subset Selection, Curse of Dimensionality, Dimensionality Reduction,
üModel Validation & Resampling Methods, Cross-validation

üModel Performance Evaluation Metrics
 
üModule 1B: Fundamentals of ML and Programming in Python (Contd.)
üProgramming in Python: Basics
üWorking with Jupyter Notebook
üScalar Objects, Type Casting
üExpressions
üStrings & String operations
üConsole Input & Output
üComparison Operators, Logic Operators
üBranching
üIteration

üFunctions
 
üModule 2: Introduction to Python for Data Science & Exploratory Data Analysis
üIntuitive statistics for Data Interpretation
üUsing Python Libraries for Data Analysis and Data Visualization
üComputing statistics, Plotting data, Interpreting results
üPractice Exercises: Analyzing datasets & Interpreting results
üModule 3: Data Munging
üData Quality Assessments
üHandling Real-World Data Issues:
üMissing Data
üDuplicate Data
üOutliers
üUnbalanced Datasets, etc.
üPractice Exercises: Fixing data quality issues in real-world datasets
üModule 4: Machine Learning Models & Applications
üFeature Engineering for Machine Learning Problems
üML Algorithms: Linear Regression, Logistic Regression, Decision Trees, Random Forests, Gradient Boosted Trees, Support Vector Machines, etc.
üPractice Exercises: Solving Regression & Classification Problems

üPractice Exercises: Solving Machine Learning Case-Studies

Course Advisors

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M/AI Expert

Why ML-AI is a must have skill for Professionals

Best Jobs of decade are coming up in the field of Machine Learning and Artificial Intelligence. ML and AI is still evolving but in the coming years, ML-AI will transcend to all the fields and thus become a must-have skill for all professionals.

Best Jobs

Learning ML-AI gives an opportunity to explore the best jobs in the Industry.

Best Salary

Data Scientists and ML-AI Professionals have most lucrative salaries in the Industry. 

Job Security

ML-AI professionals have most secured jobs in the Industry.

Entrepreneurship

Most of the fund management companies are interested in funding ML-AI startups. ML-AI Professionals have a great opportunity to explore this field.

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Do You Have Any Questions? Read Our FAQs Section and Feel Free to Ask

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