Data Science with Python Training in Austin

Name: Data Science with Python Certification Course
Item: Data Science with Python Certification Course
Rating: 5
Author: Sujit Samal

Why should you take Data Science with Python Training Course in Austin??

Python is the preferred language for new technologies such as Data Science and Machine Learning.

Data Science and Analytics (DSA) job listings is projected to grow by nearly 364,000 listings in 2020 - IBM

According to the TIOBE index, Python is one of the most popular programming languages in the world.

Introduction to Data Science and ML using Python

Topics:

Overview of Python
The Companies using Python
Different Applications where Python is Used
Discuss Python Scripts on UNIX/Windows
Values, Types, Variables
Operands and Expressions
Conditional Statements
Loops
Command Line Arguments
Writing to the Screen
What is Data Science?
What does Data Science involve?
Era of Data Science
Business Intelligence vs Data Science
Life cycle of Data Science
Tools of Data Science

Hands-On:

Creating “Hello World” code
Variables
Demonstrating Conditional Statements
Demonstrating Loops

Skills You will Learn:

Basics of Python Programming
Command Line Parameters and Flow Control in Python

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Data Handling, Sequences and File Operations

Topics:

Data Analysis Pipeline
What is Data Extraction?
Types of Data
Raw and Processed Data
Data Wrangling
Python files I/O Functions
Numbers
Strings and related operations
Tuples and related operations
Lists and related operations
Dictionaries and related operations
Sets and related operations

Hands-On:

Tuple - properties, related operations, compared with the list
List - properties, related operations
Dictionary - properties, related operations
Set - properties, related operations

Skills You will Learn:

Taking input from the user and performing operations on it
Data types in Python

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Deep Dive – Functions, OOPs, Modules, Errors, and Exceptions

Topics:

Functions
Function Parameters
Global Variables
Variable Scope and Returning Values
Lambda Functions
Object Oriented Concepts
Standard Libraries
Modules Used in Python
The Import Statements
Module Search Path
Package Installation Ways
Errors and Exception Handling
Handling Multiple Exceptions

Hands-On:

Lambda function in Python
Errors and Exceptions in Python
Packages and Modules in Python
Functions - Syntax, Arguments, Keyword Arguments, Return Values
Sorting - Sequences, Dictionaries, Limitations of Sorting

Skills You will Learn:

Object Oriented Concepts
Python Functions, Standard Libraries and Modules
Handling Exceptions in Python

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Introduction to NumPy, Pandas, and Matplotlib

Topics:

Data Analysis
NumPy - arrays
Operations on arrays
Indexing, slicing, and iterating
Reading and writing arrays on files
Pandas - data structures & index operations
Reading and Writing data from Excel/CSV formats into Pandas
Metadata for imported Datasets
Matplotlib library
Grids, axes, plots
Markers, colors, fonts, and styling
Types of plots - bar graphs, pie charts, histograms
Contour plots

Hands-On:

NumPy library - Creating NumPy array, operations performed on NumPy array
Pandas library - Creating series and data frames, Importing and exporting data
Matplotlib library - Using Scatterplot, histogram, bar graph, a pie chart to show information, Styling of Plot

Skills You will Learn:

Basic Functionalities of the NumPy library in Python
Basic Functionalities of the Pandas library in Python
Basic Functionalities of the Matplotlib library in Python

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Data Manipulation

Topics:

Basic Functionalities of a data object
Merging of Data objects
Concatenation of data objects
Types of Joins on data objects
Exploring and analyzing datasets
Analysing a dataset

Hands-On:

Pandas Function- Ndim(), axes(), values(), head(), tail(), sum(), std(), iteritems(), iterrows(), itertuples(), GroupBy operations, Aggregation, Concatenation, Merging and joining

Skills You will Learn:

Performing data manipulation using various functionalities of the Pandas library in Python

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Introduction to Machine Learning with Python

Topics:

What is Machine Learning?
Machine Learning Use-Cases
Machine Learning Process Flow
Machine Learning Categories
Linear regression
Gradient descent

Hands-On:

Linear Regression – Boston Dataset

Skills You will Learn:

Machine Learning concepts
Machine Learning types
Linear Regression Implementation

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Supervised Learning - I

Topics:

What are Classification and its use cases?
What is a Decision Tree?
Algorithm for Decision Tree Induction
Creating a Perfect Decision Tree
Confusion Matrix
What is Random Forest?

Hands-On:

Implementation of Logistic Regression, Decision Tree, Random Forest algorithms

Skills You will Learn:

Supervised Learning concepts
Implementing various Supervised Learning algorithms
Evaluating model output

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Dimensionality Reduction

Topics:

Introduction to Dimensionality
Why Dimensionality Reduction
PCA
Factor Analysis
Scaling dimensional model
LDA

Hands-On:

Introduction to Dimensionality
Why Dimensionality Reduction
PCA
Factor Analysis
Scaling dimensional model
LDA

Skills You will Learn:

Implementing Dimensionality Reduction Technique

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Supervised Learning - II

Topics:

What is Naïve Bayes?
How Naïve Bayes works?
Implementing Naïve Bayes Classifier
What is a Support Vector Machine?
Illustrate how Support Vector Machine works.
Hyperparameter Optimization
Grid Search vs. Random Search
Implementation of Support Vector Machine for Classification

Hands-On:

Implementation of Naïve Bayes, SVM algorithms

Skills You will Learn:

Supervised Learning concepts
Implementing various Supervised Learning algorithms
Evaluating model output

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Unsupervised Learning

Topics:

What is Clustering & its Use Cases?
What is K-means Clustering?
How does the K-means algorithm works?
How to do optimal clustering
What is C-means Clustering?
What is Hierarchical Clustering?
How does Hierarchical Clustering work?

Hands-On:

Implementing K-means Clustering
Implementing Hierarchical Clustering

Skills You will Learn:

Unsupervised Learning concepts
Implementation of various Clustering techniques

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Association Rules Mining and Recommendation Systems

Topics:

What are Association Rules?
Association Rule Parameters
Calculating Association Rule Parameters
Recommendation Engines
How do Recommendation Engines work?
Collaborative Filtering
Content-Based Filtering

Hands-On:

Implementing Apriori Algorithm
Performing Market Basket Analysis

Skills You will Learn:

Data Mining using Python
Recommender Systems using Python

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Reinforcement Learning (Self-Paced)

Topics:

What is Reinforcement Learning?
Why Reinforcement Learning?
Elements of Reinforcement Learning
Exploration vs. Exploitation dilemma
Epsilon Greedy Algorithm
Markov Decision Process (MDP)
Q values and V values
Q – Learning
Values

Hands-On:

Calculating Reward
Discounted Reward
Calculating Optimal quantities
Implementing Q Learning
Setting up an Optimal Action

Skills You will Learn:

Implementing Reinforcement Learning using Python
Developing Q Learning model in Python

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Time Series Analysis (Self-Paced)

Topics:

What is Time Series Analysis?
Importance of TSA
Components of TSA
White Noise
AR model
MA model
ARMA model
ARIMA model
Stationarity
ACF & PACF

Hands-On:

Checking Stationarity
Converting non-stationary data to stationary
Implementing Dickey-Fuller Test
Plotting ACF and PACF
Generating the ARIMA plot

Skills You will Learn:

TSA Forecasting in Python

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Model Selection and Boosting

Topics:

What is Model Selection?
Need for Model Selection
Cross Validation
What is Boosting?
How do Boosting Algorithms work?
Types of Boosting Algorithms
Adaptive Boosting

Hands-On:

Performing Cross Validation
Implementing AdaBoost using Python

Skills You will Learn:

Performing Model Selection
Boosting algorithms using Python

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Statistical Foundations (Self-Paced)

Topics:

What is Exploratory Data Analysis?
EDA Techniques
EDA Classification
Univariate Non-graphical EDA
Univariate Graphical EDA
Multivariate Non-graphical EDA
Multivariate Graphical EDA
Heat Maps

Hands-On:

Implementing Graphical EDA Techniques
Implementing Non-Graphical EDA Techniques

Skills You will Learn:

Performing EDA on the dataset(s) in Python

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Database Integration with Python (Self-Paced)

Topics:

Basics of database management
Python MySql
Create database
Create a table
Insert into table
Select query
Where clause
OrderBy clause
Delete query
Drop table
Update query
Limit clause
Join and Self-Join
MongoDB (Unstructured)
Insert_one query
Insert_many query
Update_one query
Update_many query
Create_index query
Drop_index query
Delete and drop collections
Limit query

Hands-On:

CRUD operations using Python MySql and MongoDB

Skills You will Learn:

Database management systems
Database Integration with Python
Working of database applications

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Data Connection and Visualization in Tableau (Self-Paced)

Topics:

Data Visualization
Business Intelligence tools
VizQL Technology
Connect to data from the File
Connect to data from the Database
Basic Charts
Chart Operations
Combining Data
Calculations

Hands-On:

Connecting to data from File, Database, and Server
Performing operations on Hierarchies, Data Granularity and Highlighting feature
Creating calculated fields using basic functions
Defining LOD expressions
Creating Parameters
Performing User Input and What-if analysis

Skills You will Learn:

Data Distribution using various charts in Tableau
Combining Data using Joins, Unions and Data Blending
Sorting, Filtering and Grouping Techniques
Table Calculations in Tableau

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Advanced Visualizations (Self-Paced)

Topics:

Trend lines
Reference lines
Forecasting
Clustering
Geographic Maps
Using charts effectively
Dashboards
Story Points
Visual best practices
Publish to Tableau Online

Hands-On:

Analyzing data using techniques including Forecasting, Trend Lines, Reference Lines, Clustering, and Geographic Maps
Building Dashboard Layout and Formatting
Building Story points

Skills You will Learn:

Advanced visualization techniques in Tableau
Building Dashboards and Stories in Tableau

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In-Class Project (Self-Paced)

Topics:

Predict the species of Plant

Hands-On:

Analyze the data.
Predict the plant species.

Skills You will Learn:

Data Pre-processing
Feature Engineering
Implementation of Machine Learning Algorithm

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Testimonial Reviews

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What is Python for Data Science?

Data is all around us, and data science will help extract the information. Data science has many applications, and python can be used to implement them. Python is a generic language that can be used to build websites, backend APIs, and scripting. Python's built-in libraries, frameworks, and tools can be used to perform various operations in data science.

Why should I learn Data Science with Python Course in Austin?

Python is definitely one of the most popular languages in Data Science, which can be used for data analysis, manipulation, and visualization. It has access to many Data Science libraries, making it the perfect language for developing applications and implementing algorithms.

Where Can I Learn Python for Data Science in Austin?

Although there are many free learning resources available, finding one that teaches data science very well is recommended. You should choose a platform that will teach you interactively and has a curriculum designed to help you along your data science journey. Edureka is one such platform as we offer the best online Data Science with Python course in Austin for data science that will take you from beginner to data analyst in Python or data scientist.

Can I learn a Python for Data Science in Austin?

Technology has made it easier and more efficient to learn online. It allows you to learn at your own pace without any barriers. Edureka's Data Science with Python certification course in Austin offers live classes and online access to study material from any location at any time. You will be able to grasp the key concepts quickly with our extensive and growing collection of tutorials, blogs, and YouTube videos. We offer a 24/7 support service to answer any questions you may have after your class ends.

What is Data Science with Python?

Data is all around us and data science will help extract the information. Data science has many applications, and python can be used to implement them. Python is a generic language which basically means that it can be used to build websites, backend APIs and scripting. Python's built-in libraries, frameworks, and tools can be used to perform various operations in data sciences.

Who are the instructors for the Python Data Science Course in Austin?

All the instructors at edureka! are practitioners from the Industry with minimum 10-12 yrs of relevant IT experience. They are subject matter experts and are trained by edureka for providing an awesome learning experience to the participants of Python Data Science Training.

Why should I learn Data Science with Python Course in Austin?

Where Can I Learn Data Science with Python Course in Austin?

Although there are many free learning resources available, finding one that teaches data science very well is recommended. You should choose a platform that will teach you interactively and has a curriculum designed to help you along your data science journey. Edureka is one such platform as we offer the best online Data Science with Python Course in Austin will take you from beginner to data analyst in Python or data scientist.

What is the Data Science with Python Course in Austin duration?

Data Science with Python Course in Austin can take between five and 10 weeks to learn basic Python programming concepts, including object-oriented programming and basic Python syntax. It is important to note that the time it takes for Python programming depends on your experience with web development, data science, and other related fields.

Can I learn a Python Data Science course online?

Technology has made it easier and more efficient to learn online. It allows you to learn at your own pace without any barriers. Edureka's Data Science with Python certification course offers live classes and online access to study material from any location at any time. You will be able to grasp the key concepts quickly with our extensive and growing collection of tutorials, blogs, and YouTube videos. We offer a 24/7 support service to answer any questions you may have after your class ends.

How will I execute practical’s in Edureka's Data Science with Python Certification Course in Austin?

You will do your Assignments/Case Studies using Jupyter Notebook, already installed on your Cloud Lab environment, whose access details will be available on your LMS. You will be accessing your Cloud Lab environment from a browser. For any doubt, the 24*7 support team will promptly assist you.

Who are the instructors for the Python Data Science Course in Austin?

All the instructors at edureka! are practitioners from the Industry with a minimum of 10-12 yrs of relevant IT experience. They are subject matter experts trained by edureka to provide an awesome learning experience to the Python Data Science Training participants in Austin.

What does a Data Science Expert do?

A Data Science Expert applies statistical, mathematical, and computational techniques to analyze and interpret large and complex datasets to extract insights, make predictions, and inform decision-making. They are skilled in programming languages like Python or R and use various tools and technologies such as machine learning algorithms, data visualization, and database systems to manipulate, process and analyze data. They may work in various industries such as finance, healthcare, marketing, etc.

What is FutureSkills Prime?

A skilling ecosystem focused on emerging technologies, powered by a partnership between the Ministry of Electronics and Information Technology, the Government of India, NASSCOM, and the IT industry. It seeks to propel India to become a global hub of talent in emerging technologies. FutureSkills Prime is one of the lighthouse schemes under the Government’s Trillion Dollar Digital Economy initiative.

How long will it take for you to learn Python for Data science in Austin?

It can take between five and 10 weeks to learn basic Python programming concepts, including object-oriented programming and basic Python syntax. It is important to note that the time it takes for Python programming depends on your experience with web development, data science, and other related fields.

What skills should a Data Science Expert know?

A Data Science Expert should have a combination of technical and non-technical skills, including:

Strong programming skills in languages like Python, R, and SQL.
Proficiency in statistical analysis, machine learning, and data visualization techniques.
Knowledge of data structures, algorithms, and database systems.
Strong problem-solving skills and ability to work with large and complex datasets.
Understanding of business processes and ability to communicate effectively with stakeholders.
Knowledge of software engineering principles for building scalable and maintainable data pipelines.
Continual learning mindset to keep up with the latest trends and technologies in the field.

What if I have more queries with regards to Data Science using Python course in Austin?

Just give us a CALL at +91 98702 76459/1844 230 6365 (US Tollfree Number) OR email at sales@edureka.co

Why FutureSkills Prime?

First of its kind government and industry partnership to drive a national skilling ecosystem for digital technologies.
End-to-end skilling from assessment to certification.
Affordable, credible content handpicked by industry leaders.
Speed up learning with bite-sized course modules.
Certifications recognized by the industry

Why is it essential to learn Data Science with Python course in Austin?

Python is preferred by data scientists over other languages because it has powerful machine learning libraries that can be used to build any machine learning algorithm. This allows for a better understanding of the current performance without sacrificing existing performance. These powerful frameworks allow data scientists to create the right neural networks. Python is the foundation of Google, YouTube and Instagram. It allows for multiple tasks to be automated and the use of these applications in various languages. The code is simple and well-documented. Many organizations are still not adopting a data-centric approach. The market lacks data literacy. To fill this gap in supply, you will need to study data science and its underlying areas by taking python data science training in Austin.

How will I get the NASSCOM FutureSkills certification?

You need to complete the modules successfully to earn a Joint Co-Branded Certificate of Completion by NASSCOM FutureSkills Prime and Edureka. On completing the course, the Learner is eligible for Government of India (GOI) incentives after successfully clearing the mandatory NASSCOM Assessment for which the learner will be awarded a NASSCOM certification. For more details please visit: https://futureskillsPrime.in/govt-of-India-incentives

Who all are eligible for the GoI incentive?

GoI Incentive can be claimed by all Indian Nationals above 18 years of age. The current programme covers beneficiaries divided into the following broad categories:

IT employees in IT Firms and Non-IT firms
Non-IT employees aspiring to use new and emerging technologies in their respective domains
Employees whose skills for a particular job have become outdated.
Central Govt. & State Govt. Employees including employees of PSUs & Autonomous bodies (Govt. Employees)
Fresh Recruits who are yet to take up a job, as well as undergoing/selected for internship & Apprenticeship roles in IT/ ITeS

How do I map my learning journey?

Mapping Your journey in 8 steps:

Enrolment in the Edureka portal
Successful completion of course modules
Quizzes, assignments and certificate project submission
Assignment and project evaluation by Edureka
Joint co-branded certificate of participation from NASSCOM and Edureka
Sign up on the FutureSkills Prime platform for mandatory FutureSkills Prime assessment
SSC Certificate issuance by Futureskills Prime on successful completion
Avail for GOI incentives upon successful completion of FutureSkills Prime assessment

What are the Job Opportunities After Completing Data Science with Python Course in Austin?

After completing a Data Science with Python course in Austin, there are various job opportunities available. Data Science is a rapidly growing field, and many industries rely on data analysis and insights for decision-making. Some job opportunities that you can explore after completing a Data Science with Python course in Austin include:

Data Scientist
Data Analyst
Machine Learning Engineer
Business Analyst
Data Engineer
Data Visualization Specialist
Predictive Analyst
Quantitative Analyst
Research Analyst
Data Science Consultant

These roles can be found in industries such as technology, finance, healthcare, e-commerce, consulting, and more. It's advisable to search for job openings on online job portals, company websites, and professional networking platforms specific to Austin to find the most relevant opportunities in the area.

What is the cost of a Data Science with Python Course in Austin?

The cost of a Data Science with Python course is $539.

What are the companies hiring Data Scientists in Austin?

There are several companies in Austin that hire Data Scientists. Some prominent companies known for their presence in the tech industry and hiring Data Scientists in Austin include:

IBM
Dell Technologies
Indeed
Oracle
Amazon
Apple
Facebook
HomeAway (Expedia Group)
Whole Foods Market (Amazon)
National Instruments

These are just a few examples, and there are many other companies in Austin across various industries such as technology, e-commerce, finance, healthcare, and more that employ Data Scientists.

What is the salary for a Data Scientist in Austin?

The average salary for a Data Scientist in Austin can vary based on factors such as experience, education, industry, and the specific company. However, on average, a Data Scientist in Austin can earn around $100,000 to $150,000 per year.

What are the other countries/cities where Edureka provides Data Science with Python courses apart from India and US?

The countries/cities where Edureka provides Data Science with Python courses are:

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Data Science with Python Training in Austin

Why should you take Data Science with Python Training Course in Austin??

Instructor-led Data Science with Python course live online classes

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Data Science with Python Course in Austin Curriculum

Introduction to Data Science and ML using Python

Data Handling, Sequences and File Operations

Deep Dive – Functions, OOPs, Modules, Errors, and Exceptions

Introduction to NumPy, Pandas, and Matplotlib

Data Manipulation

Introduction to Machine Learning with Python

Supervised Learning - I

Dimensionality Reduction

Supervised Learning - II

Unsupervised Learning

Association Rules Mining and Recommendation Systems

Reinforcement Learning (Self-Paced)

Time Series Analysis (Self-Paced)

Model Selection and Boosting

Statistical Foundations (Self-Paced)

Database Integration with Python (Self-Paced)

Data Connection and Visualization in Tableau (Self-Paced)

Advanced Visualizations (Self-Paced)

In-Class Project (Self-Paced)

Data Science Python Training in Austin Description

Why Learn Python for Data Science in Austin?

About Data Science with Python Certification Course in Austin

What are the objectives of our Data Science with Python Course in Austin?

Why Learn Data Science with Python in Austin?

Who should go for this Python Data Science Course in Austin?

What are the objectives of our Data Science with Python Course in Austin?

What are the prerequisites for this Data Science with Python Training in Austin?

Who should go for this Python Data Science and ML online course in Austin?

What are the prerequisites for this Data Science with Python Course in Austin?

How will I execute the practicals in this online Data Science with Python course in Austin?

Testimonial Reviews

Video Reviews

Python Data Science Training in Austin FAQs

What is Python for Data Science?

Why should I learn Data Science with Python Course in Austin?

Where Can I Learn Python for Data Science in Austin?

Can I learn a Python for Data Science in Austin?

What is Data Science with Python?

Who are the instructors for the Python Data Science Course in Austin?

Why should I learn Data Science with Python Course in Austin?

Where Can I Learn Data Science with Python Course in Austin?

What is the Data Science with Python Course in Austin duration?

Can I learn a Python Data Science course online?

How will I execute practical’s in Edureka's Data Science with Python Certification Course in Austin?

Who are the instructors for the Python Data Science Course in Austin?

What does a Data Science Expert do?

What is FutureSkills Prime?

How long will it take for you to learn Python for Data science in Austin?

What skills should a Data Science Expert know?

What if I have more queries with regards to Data Science using Python course in Austin?

Why FutureSkills Prime?

Why is it essential to learn Data Science with Python course in Austin?

How will I get the NASSCOM FutureSkills certification?

Who all are eligible for the GoI incentive?

How do I map my learning journey?

What are the Job Opportunities After Completing Data Science with Python Course in Austin?

What is the cost of a Data Science with Python Course in Austin?

What are the companies hiring Data Scientists in Austin?

What is the salary for a Data Scientist in Austin?

What are the other countries/cities where Edureka provides Data Science with Python courses apart from India and US?

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