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Data Science with Python Training in Austin
Data Science with Python Training in Austin
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Live Online Classes starting on 14th Sep 2024
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Why enroll for Data Science with Python course in Austin?
Data Science with Python Course in Austin 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 Austin
Live Interactive Learning
- World-Class Instructors
- Expert-Led Mentoring Sessions
- Instant doubt clearing
Lifetime Access
- Course Access Never Expires
- Free Access to Future Updates
- Unlimited Access to Course Content
24x7 Support
- One-On-One Learning Assistance
- Help Desk Support
- Resolve Doubts in Real-time
Hands-On Project Based Learning
- Industry-Relevant Projects
- Course Demo Dataset & Files
- Quizzes & Assignments
Industry Recognised Certification
- Edureka Training Certificate
- Graded Performance Certificate
- Certificate of Completion
About your Data Science with Python course
Data Science with Python Skills
Data Science with Python Tools
Data Science with Python Course Curriculum in Austin
Curriculum Designed by Experts
Edureka’s Data Science with Python Training in Austin 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 Austin, 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
![skill]( "Hands On Experience")
- Creating “Hello World” code
- Variables
- Demonstrating Conditional Statements
- Demonstrating Loops
![skill]( "skill 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
![skill]( "Hands On Experience")
- Tuple - properties, related operations, compared with the list
- List - properties, related operations
- Dictionary - properties, related operations
- Set - properties, related operations
![skill]( "skill 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
![skill]( "Hands On Experience")
- 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
![skill]( "skill 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
![skill]( "Hands On Experience")
- 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
![skill]( "skill 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
![skill]( "Hands On Experience")
- Pandas Function- Ndim(), axes(), values(), head(), tail(), sum(), std(), iteritems(), iterrows(), itertuples(), GroupBy operations, Aggregation, Concatenation, Merging and joining
![skill]( "skill 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
![skill]( "Hands On Experience")
- Linear Regression – Boston Dataset
![skill]( "skill 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?
![skill]( "Hands On Experience")
- Implementation of Logistic Regression, Decision Tree, Random Forest algorithms
![skill]( "skill 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
![skill]( "Hands On Experience")
- Implementing PCA
- Scaling dimensional model
- Implementing LDA
![skill]( "skill 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
![skill]( "Hands On Experience")
- Implementation of Naïve Bayes, SVM algorithms
![skill]( "skill 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?
![skill]( "Hands On Experience")
- Implementing K-means Clustering
- Implementing Hierarchical Clustering
![skill]( "skill 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
![skill]( "Hands On Experience")
- Implementing Apriori Algorithm
- Performing Market Basket Analysis
![skill]( "skill 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
![skill]( "Hands On Experience")
- Calculating Reward
- Discounted Reward
- Calculating Optimal quantities
- Implementing Q Learning
- Setting up an Optimal Action
![skill]( "skill 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
![skill]( "Hands On Experience")
- Checking Stationarity
- Converting non-stationary data to stationary
- Implementing Dickey-Fuller Test
- Plotting ACF and PACF
- Generating the ARIMA plot
![skill]( "skill 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
![skill]( "Hands On Experience")
- Performing Cross Validation
- Implementing AdaBoost using Python
![skill]( "skill 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
![skill]( "Hands On Experience")
- Implementing Graphical EDA Techniques
- Implementing Non-Graphical EDA Techniques
![skill]( "skill 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
![skill]( "Hands On Experience")
- CRUD operations using Python MySql and MongoDB
![skill]( "skill 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
![skill]( "Hands On Experience")
- 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
![skill]( "skill 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
![skill]( "Hands On Experience")
- Analyzing data using techniques including Forecasting, Trend Lines, Reference Lines, Clustering, and Geographic Maps
- Building Dashboard Layout and Formatting
- Building Story points
![skill]( "skill 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
![skill]( "Hands On Experience")
- Analyze the data
- Predict the plant species
![skill]( "skill you will learn")
- Data Pre-processing
- Feature Engineering
- Implementation of Machine Learning Algorithm
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Data Science Python Training in Austin Description
Edureka provides extensive Data Science with Python training in Austin 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 Austin.
Why Learn Python for Data Science in Austin?
description: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.
About Data Science with Python Certification Course in Austin
Edureka’s Data Science with Python Certification Training in Austin 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 objectives of our Data Science with Python Course in Austin?
After completing this Data Science using Python Certification course in Austin, 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.
Why Learn Data Science with Python in Austin?
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.
Who should go for this Python Data Science Course in Austin?
Edureka’s Data Science with Python Course in Austin 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 objectives of our Data Science with Python Course in Austin?
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.
What are the prerequisites for this Data Science with Python Training in Austin?
The pre-requisites for Edureka's Python Data Science course training in Austin include 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.
Who should go for this Python Data Science and ML online course in Austin?
- 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
What are the prerequisites for this Data Science with Python Course in Austin?
The prerequisites for Edureka's Python Data Science and ML course training include the fundamental understanding of Computer Programming Languages.
How will I execute the practicals in this online Data Science with Python course in Austin?
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 Course in Austin Projects
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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.
You do not need a coding background to enroll in this Data Science with Python course in Austin. 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.
- 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 Austin to help you prepare for job interviews.
GoI Incentive can be claimed by all Indian Nationals above 18 years of age. The current program 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
Right after the completion of this Data Science with Python course in Austin, 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.
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Python Data Science Training in Austin FAQs
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?
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 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
- 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.
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