This document describes training courses offered by Object Automation on futuristic technologies like machine learning, artificial intelligence, and data science. It provides overviews and details on 4 courses that make up its data science program: Machine Learning Fundamentals, Introduction to Artificial Intelligence, Python for Data Science, and Big Data Analytics Using Spark. Each course is 12-15 weeks long and involves 8-10 hours of work per week. The program prepares students for in-demand jobs in data science, machine learning, and artificial intelligence.

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INDUSTRY READY
TRAINING by OA

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HELLO!We’re Object Automation
we here love to equip you with
knowledge on futuristic
technologies.
You can find us
@object-automation.com
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COURSE OVERVIEW
MACHINE LEARNING FUNDAMENTALS
Understand machine learning’s role in data-
driven modeling, prediction, and decision-
making.
INTRODUCTION TO ARTIFICIAL INTELLIGENCE
Brief introduction to neural networks,NLP,Image
classification,text recognition,deep learning.
PYTHON FOR DATA SCIENCE
Learn to use powerful, open-source,
Python tools, including Pandas, Git and
Matplotlib, to manipulate, analyze, and
visualize complex datasets
BIG DATA ANALYTICS USING SPARK
Understand machine learning’s role in
data-driven modeling, prediction, and
decision-making.
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AVERAGE LENGTH : 10 - 15 WEEK PER COURSE 4 COURSE IN A PROGRAM
EFFORT : 8- 10 HOURS PER WEEK

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“Information is the oil of 21st
century, and analytics is the
combustion engine ”
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Job Outlook
● There are approximately 215,000 open job positions in Data
Science (Source:Indeed.com)
● There are currently about 31,000 openings for Statistician
positions in the US (LinkedIn), offering an average salary of
$77,000 (Glassdoor)
● In the field of Business intelligence, there are around 14,000
openings in the US (LinkedIn) at a $88,000 base salary
● Careers include data scientist, data engineer, data analyst,
statistician, data manager, data architect, business analyst
● Data Scientist is rated the best job in America for 2017, with
a median base salary of $110,000. (Source: Glassdoor)
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PATHWAY TO FUTURISTIC JOB
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12-15
WEEK
INTRODUCTION TO
ARTIFICIAL INTELLIGENCE
12-15
WEEK
BIG DATA ANALYTICS
USING SPARK
12 - 15
WEEK
MACHINE LEARNING
FUNDAMENTALS
12 - 15
WEEK
PYTHON FOR DATA
SCIENCE

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“What you’ll Learn:
● How to load and clean real-world data
● How to make reliable statistical inferences from noisy
data
● How to use machine learning to learn models for data
● How to visualize complex data
● How to use Apache Spark to analyze data that does
not fit within the memory of a single computer
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PYTHON FOR DATA SCIENCE
Let’s start with the first step

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Python for data science
● python
● jupyter notebooks
● pandas
● numpy
● matplotlib
● git
● and many other tools
Learn to use powerful, open-source, Python tools,
including Pandas, Git and Matplotlib, to manipulate,
analyze, and visualize complex datasets.
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BIG DATA
CONCEPT
Learn how to analyze large datasets using Jupyter
notebooks, MapReduce and Spark as a platform
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What you'll learn
● Programming Spark using Pyspark
● Identifying the computational tradeoffs in a Spark
application
● Performing data loading and cleaning using Spark and
Parquet
● Modeling data through statistical and machine learning
methods

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MACHINE
LEARNING
FUNDAMENTALS
Understand machine learning’s role in data-driven
modeling, prediction, and decision-making
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What you'll learn
● Classification, regression, and conditional probability
estimation
● Generative and discriminative models
● Linear models and extensions to nonlinearity using kernel
methods
● Ensemble methods: boosting, bagging, random forests
● Representation learning: clustering, dimensionality
reduction, autoencoders, deep nets

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Do you want to build systems
that learn from experience? Or
exploit data to create simple
predictive models of the world?
In this course, part of
the Data Science
program, you will learn
a variety of supervised
and unsupervised
learning algorithms,
and the theory behind
those algorithms
Armed with the
knowledge from this
course, you will be able
to analyze many
different types of data
and to build descriptive
and predictive models
All programming
examples and
assignments will be in
Python, using Jupyter
notebooks
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Probability and Statistics in
Data Science using Python
Using Python, learn
statistical and probabilistic
approaches to understand
and gain insights from data.
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Clients and Partners