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Data Science with Python Training in Dallas

Data Science with Python Training in Dallas
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Live Online Classes starting on 14th Dec 2024
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Instructor-led Mastering Python live online Training Schedule

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Why enroll for Data Science with Python course in Dallas?

pay scale by Edureka coursePython is the preferred language for new technologies such as Data Science and Machine Learning.
IndustriesData Science and Analytics (DSA) job listings is projected to grow by nearly 364,000 listings in 2020 - IBM
Average Salary growth by Edureka courseAccording to the TIOBE index, Python is one of the most popular programming languages in the world.

Data Science with Python Course in Dallas Benefits

Data science job opportunities are projected to increase by 30% annually, and proficiency in Python programming and data science can unlock vast job prospects. The rise in demand for skilled data scientists and machine learning engineers has prompted more businesses to incorporate machine learning into their operations and help companies analyze and process data, leading to quick and effective decision-making. Obtaining a Data Science and ML Certification from Edureka is the optimal way to secure a lucrative job in this field.
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Why Data Science with Python course from edureka in Dallas

Live Interactive Learning

Live Interactive Learning

  • World-Class Instructors
  • Expert-Led Mentoring Sessions
  • Instant doubt clearing
Lifetime Access

Lifetime Access

  • Course Access Never Expires
  • Free Access to Future Updates
  • Unlimited Access to Course Content
24x7 Support

24x7 Support

  • One-On-One Learning Assistance
  • Help Desk Support
  • Resolve Doubts in Real-time
Hands-On Project Based Learning

Hands-On Project Based Learning

  • Industry-Relevant Projects
  • Course Demo Dataset & Files
  • Quizzes & Assignments
Industry Recognised Certification

Industry Recognised Certification

  • Edureka Training Certificate
  • Graded Performance Certificate
  • Certificate of Completion

About your Data Science with Python course

Data Science with Python Skills

  • skillPython Programming
  • skillStatistical Foundations
  • skillData Analysis and Visualization
  • skillSupervised and Unsupervised Machine Learning
  • skillDatabase Integration with Python
  • skillData Visualization Using Tableau

Data Science with Python Tools

  • Python
  • Jupyter
  • Scikit-Learn
  • NumPy
  • Pandas
  • matplotlib
  • mongoDB

Data Science with Python Course Curriculum in Dallas

Curriculum Designed by Experts

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Edureka’s Data Science with Python Training in Dallas will provide hands-on experience in Python programming. We offer live-instructor-led sessions which will help you in mastering the concepts involved in Python. With Edureka’s Data Science Python training in Dallas, you will learn the essential concepts of Python programming such as Data Structure, Data types, Strings, tuples, lists, basic operators and functions, GUIs, Multi-threading, Data Manipulation, Expressions, Networking, Lambda expressions and much more. Also, in this Data Science Python course, you will gain a thorough knowledge of Python OOPS concepts, modules, Django framework, Database programming, and connectivity to multiple data sources.

Introduction to Data Science and ML using Python

16 Topics

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

skillHands-on:

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

skillSkills You will Learn:

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

Data Handling, Sequences and File Operations

12 Topics

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

skillHands-on:

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

skillSkills You will Learn:

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

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

13 Topics

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

skillHands-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

skillSkills You will Learn:

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

Introduction to NumPy, Pandas, and Matplotlib

13 Topics

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

skillHands-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

skillSkills 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

Data Manipulation

5 Topics

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

skillHands-on:

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

skillSkills You will Learn:

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

Introduction to Machine Learning with Python

6 Topics

Topics:

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

skillHands-on:

  • Linear Regression – Boston Dataset

skillSkills You will Learn:

  • Machine Learning concepts
  • Machine Learning types
  • Linear Regression Implementation

Supervised Learning - I

6 Topics

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?

skillHands-on:

  • Implementation of Logistic Regression, Decision Tree, Random Forest algorithms

skillSkills You will Learn:

  • Supervised Learning concepts
  • Implementing various Supervised Learning algorithms
  • Evaluating model output

Dimensionality Reduction

6 Topics

Topics:

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

skillHands-on:

  • Implementing PCA
  • Scaling dimensional model
  • Implementing LDA

skillSkills You will Learn:

  • Implementing Dimensionality Reduction Technique

Supervised Learning - II

8 Topics

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

skillHands-on:

  • Implementation of Naïve Bayes, SVM algorithms

skillSkills You will Learn:

  • Supervised Learning concepts
  • Implementing various Supervised Learning algorithms
  • Evaluating model output

Unsupervised Learning

7 Topics

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?

skillHands-on:

  • Implementing K-means Clustering
  • Implementing Hierarchical Clustering

skillSkills You will Learn:

  • Unsupervised Learning concepts
  • Implementation of various Clustering techniques

Association Rules Mining and Recommendation Systems

7 Topics

Topics:

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

skillHands-on:

  • Implementing Apriori Algorithm
  • Performing Market Basket Analysis

skillSkills You will Learn:

  • Data Mining using Python
  • Recommender Systems using Python

Reinforcement Learning (Self-Paced)

9 Topics

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

skillHands-on:

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

skillSkills You will Learn:

  • Implementing Reinforcement Learning using Python
  • Developing Q Learning model in Python

Time Series Analysis (Self-Paced)

10 Topics

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

skillHands-on:

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

skillSkills You will Learn:

  • TSA Forecasting in Python

Model Selection and Boosting

7 Topics

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

skillHands-on:

  • Performing Cross Validation
  • Implementing AdaBoost using Python

skillSkills You will Learn:

  • Performing Model Selection
  • Boosting algorithms using Python

Statistical Foundations (Self-Paced)

8 Topics

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

skillHands-on:

  • Implementing Graphical EDA Techniques
  • Implementing Non-Graphical EDA Techniques

skillSkills You will Learn:

  • Performing EDA on the dataset(s) in Python

Database Integration with Python (Self-Paced)

22 Topics

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

skillHands-on:

  • CRUD operations using Python MySql and MongoDB

skillSkills You will Learn:

  • Database management systems
  • Database Integration with Python
  • Working of database applications

Data Connection and Visualization in Tableau (Self-Paced)

9 Topics

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

skillHands-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

skillSkills 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

Advanced Visualizations (Self-Paced)

10 Topics

Topics:

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

skillHands-on:

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

skillSkills You will Learn:

  • Advanced visualization techniques in Tableau
  • Building Dashboards and Stories in Tableau

In-Class Project (Self-Paced)

1 Topics

Topics:

  • Predict the species of Plant

skillHands-on:

  • Analyze the data
  • Predict the plant species

skillSkills You will Learn:

  • Data Pre-processing
  • Feature Engineering
  • Implementation of Machine Learning Algorithm

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Data Science Python Training in Dallas Description

Edureka provides extensive Data Science with Python training in Dallas to assist you in mastering basics with sophisticated theoretical ideas such as writing scripts, sequence, and file procedures in Python while gaining practical experience with functional apps. This Data Science training is combined with hands-on tasks and live projects. Python is a common high-level, open-source programming language with a broad spectrum of apps for games and web applications in automation, big data, data science, and information analytics development. It's a versatile, powerful, object-oriented and interpreted language that you will learn during this Data Science with Python course in Dallas.

About Data Science with Python Certification Course in Dallas

Edureka’s Data Science with Python Certification Training in Dallas is designed to make you grasp the concepts of Data Science and Machine Learning. As a data scientist, you will learn the importance of machine learning and its implementation in the Python programming language. You will be able to automate real-life scenarios using machine learning algorithms, and towards the end of this course, we will be discussing various practical use cases of machine learning with the Python programming language to enhance your learning experience. Edureka offers the best Data Science with Python training online for those who want to be the best in Python. Enroll now in Edureka's online Data Science with Python Certification to get trained by industry experts.

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

    The prerequisites for Edureka's Python Data Science and ML course training include the fundamental understanding of Computer Programming Languages.

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

      After completing this Data Science with 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 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
      • Explain Time Series and its related concepts
      • Perform Text Mining and Sentiment analysis

      Edureka offers the best online course for Python data science and ML. Enroll now in our Data Science with Python training and get a chance to learn from industry leaders.

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

        • Freshers, 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

        Why Learn Data Science with Python in Dallas?

        Python has been one of the premier, flexible, and powerful open-source languages that are easy to learn, easy to use, and powerful libraries for data manipulation and analysis. It has been used for over a decade in scientific computing and highly quantitative domains such as finance, oil and gas, physics, and signal processing. It continues to be a favorite option for data scientists who build and use 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 into the most preferred Language for Data Analytics. The increasing search trends also indicate that it is the Next Big Thing and a must for professionals in the data analytics domain.

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

          You will do your assignments and case studies using Jupyter Notebook, which is already installed on your Cloud LAB environment (access it from a browser). The access credentials are available on your LMS. Should you have any queries, the 24*7 Support Team will promptly assist you.

            Data Science with Python Certification in Dallas Projects

            certification projects

            Industry: Automobile

            Riding the digital wave, India's used car market is set to grow at a compounded annual growth of 11% and likely to touch sales of up to 8.3 million units by FY26 as more people h....
            View Project Details
            certification projects

            Industry: Healthcare

            Heart Disease is among the most prevalent chronic diseases in the United States, impacting millions of Americans each year and exerting a significant financial burden on the econ....
            View Project Details

            Data Science with Python Certification in Dallas

            You need to complete the modules successfully to earn a Joint Co-Branded Certificate of Participation 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
            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.
            • 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.

            Yes, we offer a practice test in the Data Science with Python course in Dallas to help you prepare for job interviews.
            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

            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

            You do not need a coding background to enroll in this Data Science with Python course in Dallas. The course begins with beginner modules in which we cover the fundamentals of Python coding. In fact, you do not need prior knowledge in Data Science and Machine Learning either. All relevant topics are a part of this course from scratch. 
            Right after the completion of this Data Science with Python course in Dallas, you will obtain a certificate and will be eligible to apply for junior or associate data scientist jobs. After gaining some work experience, you can become a Senior Data Scientist or Machine Learning Engineer. This Edureka online course offers you the opportunity to connect with expert industry instructors to guide you through your desired career path.
            Please visit the page which will guide you through the top 100+ Data Science Interview Questions with answers.
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            Python Data Science Training in Dallas FAQs

            What is Python for Data Science in Dallas?

            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 Dallas?

            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 Dallas?

            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 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 Dallas?

            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 Data Science with Python Course in Dallas?

            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.

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

            Data Science with Python Course 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.

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

            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. 

            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.

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

            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.

            Which kind of projects will be a part of this Data Science with Python Certification Course in Dallas?

            Project Title: Consumer Complaint Resolution 
            Problem Statement: Predicting which complaints have a higher potential to be disputed and identifying systematic issues can help enhance the quality of communication and satisfactory resolution.

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

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

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

            What are the companies hiring Data Scientists in Dallas?

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

            1. AT&T

            2. Capital One

            3. Southwest Airlines

            4. American Airlines

            5. Texas Instruments

            6. JPMorgan Chase

            7. Verizon

            8. Cognizant

            9. Toyota

            10. Amazon

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


            What is the salary for a Data Scientist in Dallas?

            The average salary for a Data Scientist in Dallas can vary based on factors such as experience, education, industry, and the specific company. However, on average, a Data Scientist in Dallas can earn around $95,000 to $150,000 per year.

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