Data Science with Python Training in Charlotte

Name: Data Science with Python Certification Course
Item: Data Science with Python Certification Course
Rating: 5
Author: Raghava Beeragudem

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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Why Learn Python for Data Science in Charlotte?

Python has been one of the premier, flexible, and powerful open-source languages that is easy to learn, easy to use, and has powerful libraries for data manipulation and analysis. For over a decade, It has been used in scientific computing and highly quantitative domains such as finance, oil and gas, physics, and signal processing. It's continued to be a favourite option for data scientists who use it for building and using Machine learning applications and other scientific computations. Python cuts development time in half with its simple to read syntax and easy compilation feature. Debugging programs is a breeze in Python with its built in debugger. It has evolved as the most preferred Language for Data Analytics and the increasing search trends also indicate that it is the Next Big Thing and a must for Professionals in the Data Analytics domain.

What are the objectives of our Data Science with Python Training in Charlotte?

After completing this Data Science using Python Certification course, you will be able to:

Programmatically download and analyze data
Learn techniques to deal with different types of data – ordinal, categorical, encoding
Learn data visualization
Using I python notebooks, master the art of presenting step by step data analysis
Gain insight into the 'Roles' played by a Machine Learning Engineer
Describe Machine Learning
Work with real-time data
Learn tools and techniques for predictive modeling
Discuss Machine Learning algorithms and their implementation
Validate Machine Learning algorithms
Perform Text Mining and Sentimental analysis
Explain Time Series and its related concepts
Gain expertise to handle business in future, living the present

Edureka offers the best online course for Python Data Science. Enroll now with our data Science with Python training and get a chance to learn from industrial giants.

Who should go for this Python Data Science online course in Charlotte?

Edureka’s course is a good fit for the below professionals:

Programmers, Developers, Technical Leads, Architects
Developers aspiring to be a ‘Machine Learning Engineer'
Analytics Managers who are leading a team of analysts
Business Analysts who want to understand Machine
Learning (ML) Techniques
Information Architects who want to gain expertise in
Predictive Analytics
Professionals who want to design automatic predictive models

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

The pre-requisites for Edureka's Python Data Science course training in Charlotte includes the fundamental understanding of Computer Programming Languages. Fundamentals of Data Analysis practiced over any of the data analysis tools like SAS/R will be a plus. However, you will be provided with complimentary “Python Statistics for Data Science” as a self-paced course once you enroll for the Data Science with Python certification course.

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What is Python for Data Science in Charlotte?

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 Charlotte?

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 Charlotte?

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 Charlotte 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 online in Charlotte?

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.

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

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 Data Science with Python Course in Charlotte.

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

Data Science with Python Course in Charlotte 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 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.

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

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.

What type of job can I get after completing a Data Science with Python course in Charlotte?

This is an industry where opportunities are plenty, so once you have the education and qualifications, the jobs are waiting for you. To name a few, some of the most common job titles for data scientists include:

Business Intelligence Analyst
Data Mining Engineer
Data Architect
Data Scientist
Senior Data Scientist

What are the companies hiring Data Scientists in Charlotte?

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

Bank of America
Wells Fargo
Duke Energy
LendingTree
Lowe's
AvidXchange
TIAA
Ally Financial
Brighthouse Financial
Sealed Air

These are just a few examples, and there are many other companies in Charlotte across various industries such as banking, finance, energy, technology, and more that employ Data Scientists.

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

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

What is the salary for a Data Scientist in Charlotte?

The average salary for a Data Scientist in Charlotte can vary based on factors such as experience, education, industry, and the specific company. However, on average, a Data Scientist in Charlotte can earn around $90,000 to $140,000 per year.

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Testimonial Reviews

Sudhiranjan SarmaAnalytics and Information management, Cognizant

My experience with edureka about Python is much impressed, with such quality of the training. We get ... Read More

Sidhartha MitraIBM MDM COE Head @ CTS, Kolkata Area, India

Edureka has been an unique and fulfilling experience. The course contents are up-to-date and the ins ... Read More

Sarvani KareSr. Software developer, Lockheed Martin Information Technology, Baltimore, Maryland Area

Very good courses covering lots of topics. Excellent class delivery and lecture notes. I really lear ... Read More

Praveen KonkisaBI Architect & Hadoop Specialist at Teradata

I have taken Informatica, Hadoop, R-programming, Spark and Scala and several other training's from p ... Read More

Raghava BeeragudemSenior Big Data Consultant at Clarity Solution Group

I have taken 3 courses (Hadoop development, Python and Spark) in last one year. It was an excellent ... Read More

AalapIntegrations, Developer Support, Engineering

Clean, simple and a fantastic learning resource. The courses are a great resource for personal devel ... Read More

Video Reviews

Vinayak shares his Edureka learning experience and how our Big Data training helped him achieve his dream career path.

Sriram speaks about his learning experience with Edureka and how our Hadoop training helped him execute his Big Data project efficiently.

Our learner Balasubramaniam shares his Edureka learning experience and how our training helped him stay updated with evolving technologies.

Data Science with Python Training in Charlotte

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

Instructor-led Data Science with Python course live online classes

Financing Options

Data Science with Python Course in Charlotte 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 Charlotte Description

Why Learn Python for Data Science in Charlotte?

What are the objectives of our Data Science with Python Training in Charlotte?

Who should go for this Python Data Science online course in Charlotte?

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

Testimonial Reviews

Video Reviews

Python Data Science Training in Charlotte FAQs

What is Python for Data Science in Charlotte?

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

Where Can I Learn Python for Data Science in Charlotte?

Can I learn a Python for Data Science online in Charlotte?

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

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

What does a Data Science Expert do?

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

What type of job can I get after completing a Data Science with Python course in Charlotte?

What are the companies hiring Data Scientists in Charlotte?

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

What is the salary for a Data Scientist in Charlotte?

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