4Achievers is a leading Data Science Training Institute in Gurgaon that offers industry-standard training programs designed to make students proficient in data science. The course provides practical learning with an emphasis on real-world applications and problem-solving techniques using the latest tools and technologies. With expert mentors and world-class infrastructure, 4Achievers ensures that students are well-prepared for a successful career in the data science field.
At 4Achievers, we believe in learning through experience, and therefore, our Data Science Training in Gurgaon involves live projects that give students a chance to work on industry-relevant problems. Our strong focus on placement assistance and personalized mentoring ensures that each student gets the right support throughout their learning journey.
Live Projects:
Placement Assistance:
World-Class IT Lab Facilities:
Feature | Benefit |
---|---|
Experienced Trainers | Learn from industry professionals with years of experience. |
Real-World Projects | Work on live projects that mirror real job scenarios. |
Comprehensive Curriculum | Covers everything from statistics to machine learning and big data. |
Flexible Timings | Weekend and weekday batches for working professionals. |
At 4Achievers, a leading Data Science Training Institute in Gurgaon, we incorporate Agile methodologies to enhance the learning experience during our Data Science courses. Agile practices help students learn how to manage projects in a collaborative, efficient, and iterative manner, which is essential for real-world data science work.
Daily Standups
A short meeting where students share their progress, challenges, and goals for the day. This helps track progress and encourages accountability.
Sprint Planning
At the start of each sprint (a set period of time), students plan their tasks, breaking them into smaller, manageable pieces. This is crucial for working on large datasets or machine learning projects.
Sprint Review
After completing each sprint, students present their work to peers and instructors for feedback, allowing for course correction and improvement.
Sprint Retrospective
Students reflect on what went well and what didn’t, discussing how to improve the next sprint.
Activity | Purpose | Key Benefit |
---|---|---|
Daily Standups | Track progress and obstacles | Keeps students aligned and focused |
Sprint Planning | Organize tasks and set goals | Increases productivity and focus |
Sprint Review | Receive feedback and improve | Ensures continuous learning |
Sprint Retrospective | Reflect on the process | Fosters continuous improvement |
Incorporating Agile practices in the Data Science Training at 4Achievers equips students with the practical skills needed to thrive in data-driven environments.
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4Achievers are delighted to announce our next application cycle for the 4Achievers Data Science Summer internship program in Gurgaon, India. We are looking for talented and passionate individuals who share our vision for transforming India's workforce by uniting people across industries and understanding what makes them tick.
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If you're interested in an interesting Winter internship and getting hands-on experience working on cutting-edge technologies, then 4Achievers is the company for you. We are currently accepting applications for a Data Science winter internship in Gurgaon 2024. 4Achievers interns will gain invaluable experience working with some of the world's leading companies, including Google, Microsoft, and Facebook. They will work on real-world problems involving big data analytics and machine learning, gaining an understanding of how these technologies can be applied to improve business processes and operations.
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Data quality is essential to data science because it is the foundation of reliable and accurate analysis. Good data quality means data is complete, accurate, valid, and consistent. Data science relies on clean, accurate, and up-to-date data to produce meaningful insights. Poor data quality can lead to inaccurate conclusions, incorrect decisions, or a lack of trust in the data and analysis. Data quality assurance is a key component of data science, as data scientists must ensure their datasets are of the highest quality before they can be used for analysis. Data quality assurance includes activities such as data cleaning, data validation, data enrichment, and data profiling. These activities help identify and correct any errors or inconsistencies in the data, and ensure data completeness and accuracy. Data quality is also important for data governance, as it helps ensure data is consistent and secure, and that data privacy and compliance standards are met. Data quality is essential in data science and must be taken seriously to ensure reliable and meaningful analysis.
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Supervised learning is a type of machine learning algorithm where the model is initially trained and fed with labeled training data in order to learn from it. Labeled data contains a set of input variables and a corresponding output set, which allows the model to learn the mapping between the two. Supervised learning requires that the model be given a large number of labeled examples in order for it to accurately predict the output for new data.
Semi-supervised learning is a type of machine learning algorithm that combines both supervised and unsupervised learning. Semi-supervised learning allows the model to use a small amount of labeled data combined with a large amount of unlabeled data in order to learn patterns in the data. This allows the model to make more accurate predictions than with only labeled data, while still requiring less data than a fully supervised learning algorithm.
Data preparation is an essential step in the data science process. 4Achievers involves the cleaning, transformation, and enrichment of data to make it suitable for use in analysis, machine learning, or other operations. 4Achievers is the process of gathering, cleaning, and organizing data to make it ready for use in analysis or modeling. Data preparation helps ensure that the data is accurate, complete, and of the right quality for analysis or modeling. By taking the time to prepare the data, data scientists can avoid costly mistakes and ensure that they have the best data to work with. Data preparation can also help reduce the time and effort needed to analyze the data by ensuring that the data is in the right format and of the highest quality. Finally, data preparation can help to uncover trends and patterns in the data that may not have been visible before.
Data wrangling in data science is the process of gathering, cleaning, organizing, and transforming data into a usable format for analysis. 4Achievers involves combining and manipulating data from multiple sources, such as databases, spreadsheets, and APIs, into a consistent format. Data wrangling helps to ensure data is in the right format and ready for analysis, as well as to identify potential problems such as missing data, incorrect data types, and inconsistencies. Data wrangling also helps to uncover hidden insights, enabling analysts to make data-driven decisions and generate compelling visualizations. By refining and preparing data, data wrangling helps data scientists to gain deeper insights from their data.
Data security is a critical component of data science. 4Achievers ensures that the data being analyzed is secure from unauthorized access and manipulation. Data security also ensures the accuracy and completeness of the data being analyzed, preventing malicious actors from altering or deleting important information. With data security, data scientists can be sure that their data is safe, secure, and reliable.
Data security is especially important in data science because it ensures the accuracy and integrity of the data being used in the analysis. 4Achievers also helps to protect the data from being corrupted, manipulated, or stolen. Data security can help to prevent data breaches, which can be costly for organizations and individuals.
Data security also helps to ensure the privacy and confidentiality of the data being analyzed. 4Achievers can protect sensitive information from being exposed to unauthorized individuals or entities. Furthermore, data security can help to protect against cyber-attacks, which can be devastating for organizations and individuals.
Overall, data security is an essential component of data science. 4Achievers helps to ensure the accuracy and integrity of the data being analyzed and helps to protect the data from being exposed to malicious actors. Data security is a key factor in ensuring the security and reliability of the data being used in data science projects.
Natural language processing (NLP) is a branch of data science that focuses on enabling computers to interpret, analyze, and generate human language. 4Achievers is used to analyze large amounts of unstructured text data, such as audio, video, and written text, and to derive insights from it. NLP can be used to identify topics in text data, analyze sentiment, and extract information from text, as well as to generate natural language summaries of data. With NLP, data scientists can gain insights into customer sentiment, trends, and other valuable information from unstructured text data that was previously difficult to process. NLP can help data scientists to better understand customer needs, improve marketing strategies, and gain insights for predictive analytics.
Data analysis techniques can be broadly divided into two categories: quantitative and qualitative. Quantitative techniques involve the use of numerical data and statistical methods to analyze data. Examples of quantitative techniques include descriptive statistics, exploratory data analysis, linear regression, correlation analysis, and survival analysis. Qualitative techniques involve the use of non-numerical data, such as interviews, questionnaires, or focus groups, to analyze data. Examples of qualitative techniques include content analysis, discourse analysis, ethnography, and case studies. Both quantitative and qualitative techniques can be used to gain insights into data and understand patterns and trends.
Data science and data engineering both involve working with data, but they are two distinct disciplines with different roles. Data science is a field of study focused on exploring, analyzing, and interpreting data in order to uncover insights and to develop predictive models. 4Achievers involves the use of various techniques such as machine learning, natural language processing, statistics, and data visualization to extract valuable information from data. Data engineering, on the other hand, is a field of study focused on developing, managing, and maintaining data pipelines, databases, and other data systems. 4Achievers involves the use of software engineering principles and technologies to build data-driven systems, such as data warehouses and data lakes. Data engineering is often used to support the work of data scientists by providing them with the necessary data infrastructure and ensuring that their data is properly stored, accessed, and processed. In summary, data science focuses on analyzing and interpreting data, while data engineering focuses on developing and managing data systems.
Data governance is an essential component of data science. 4Achievers is the process of establishing and maintaining control over the collection, storage, use, and dissemination of data. 4Achievers primary goal of data governance is to ensure that data is accurate, consistent, and secure.
Data governance is necessary in order to ensure the integrity of the data collected and used in data science projects. 4Achievers helps to ensure that data is accurate, consistent, and secure. Data governance also helps to ensure that data is used responsibly and that its use complies with relevant regulations or laws.
Data governance is necessary for data scientists to build trust with their data sources. 4Achievers helps to ensure that data sources are properly validated and that data is collected in a way that is ethical and compliant with relevant regulations. Data governance provides guidelines for data collection, storage, use, and dissemination, which helps to ensure that data is secure and its use is compliant with relevant laws and regulations.
Data governance also ensures that data is properly organized and accessible, so that data scientists can find the information they need quickly and accurately. Good data governance helps to reduce the risk of data misuse or data breaches, which can have significant consequences for both organizations and individuals.
Finally, data governance helps to increase the efficiency of data scientists. Good data governance can help data scientists to quickly access the data they need and to work with it more efficiently. This can help to reduce the time and effort needed to complete data science projects, while also ensuring that the results are accurate.
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4Achievers Data Science Training program at 4Achievers is designed to provide individuals with the necessary skills and knowledge to become successful data scientists. To join the program, applicants should have basic knowledge of mathematics and statistics, as well as a strong interest in data science. Experience in coding and programming languages such as R, Python, and SQL is highly recommended, although not required. Additionally, applicants should be comfortable working with data structures and algorithms. Although familiarity with machine learning is beneficial, it is not a requirement. Furthermore, it is also recommended that applicants have a good understanding of the fundamentals of databases and data visualization. 4Achievers ability to think critically and creatively to solve complex problems is a must. Finally, the ability to work independently and collaboratively with others is important for success in the program.
Yes, 4Achievers provides guidance on data analysis during its Data Science Training program. 4Achievers program covers topics such as data gathering and preparation, data exploration, data visualization, predictive analytics, machine learning, and data mining. Through this program, students gain the skills and knowledge to identify, analyze, and interpret data to help organizations make better decisions. 4Achievers course also offers practical exercises that allow students to apply the concepts they learn in the classroom. Students are able to work with real-world data sets and gain hands-on experience. Furthermore, experienced professionals in the field provide mentorship and guidance throughout the training. This helps students to gain an in-depth understanding of data analysis and apply it to their own projects.
4Achievers Data Science Training program offered by 4Achievers offers guidance on data visualization. This is done through the use of lectures, tutorials, and hands-on workshops. During the lectures, instructors explain the fundamentals of data visualization, including visualizing data with charts, graphs, and tables. 4Achievers tutorials allow students to practice using data visualization software and explore the data analysis process. In the hands-on workshops, students are guided through the process of creating data visualizations, from concept to implementation. Through this approach, students gain an understanding of the importance of data visualization, and how to apply it to their data analysis.
4Achievers provides comprehensive guidance on machine learning during its Data Science Training Program. During the program, learners are introduced to machine learning concepts and terminology, and then guided through the process of applying them to real-world data. Trainers provide hands-on guidance, helping learners to understand how to develop machine learning algorithms, identify and select the best algorithms for their dataset, and interpret the results. Learners gain an understanding of the various types of machine learning algorithms, and learn to apply them to their data sets. Additionally, learners are taught important tips and best practices to ensure successful model development. 4Achievers program also provides plenty of opportunities to practice and hone their machine learning skills.
4Achievers offers the most comprehensive Data Science Training Program with a focus on deep learning. 4Achievers program covers a wide range of topics that include data analysis, machine learning, and deep learning. 4Achievers course is designed to provide the students with a solid foundation for understanding and applying deep learning concepts. 4Achievers program also provides hands-on practical experience with programming and application development, and the instructors are industry experts in the field of deep learning. 4Achievers course also includes lecture-style sessions and online resources to give students better understanding of the concepts. Finally, the program provides real-world examples, projects, and case studies to help students gain a better understanding of deep learning.
4Achievers provides guidance on data mining during the Data Science Training Program by providing an overview of the process and teaching the basics of how to use tools such as Python and SQL to extract, manipulate and analyze data. Participants will learn how to employ data mining techniques to identify patterns in data and use the insights gained to make informed decisions. 4Achievers training program also covers the different types of data mining algorithms and how to interpret results. 4Achievers program also provides hands-on experience to help participants gain the necessary skills to utilize data mining on their own.
Yes, the Data Science Training program offered by 4Achievers is comprehensive and up-to-date. 4Achievers covers the latest trends in data science and provides the necessary skills and knowledge to help learners develop their expertise in this field. 4Achievers is also constantly updated to ensure that it remains current and relevant.
Yes, 4Achievers provides support for its Data Science Training program after completion. They provide career counseling and guidance to help students find the right job opportunity after completion of the training program. They also provide certification programs to help students validate their knowledge and skills. Additionally, 4Achievers offers students the opportunity to interact with industry professionals, attend seminars and workshops, and access online resources to stay up to date with the latest trends in the data science industry. Furthermore, the company provides personalized feedback and mentorship to help students further develop their skills. All of these resources are available to students to make sure they have the right resources to excel in the data science industry.
4Achievers' Data Science Training program provides guidance on the use of data science tools. Firstly, the program covers the fundamentals of data science and its related tools, such as Python, R and SQL. Secondly, the program focuses on practical applications of these tools, including data pre-processing, data analysis and visualization, machine learning, deep learning and natural language processing. Thirdly, the program provides hands-on experience on data science projects with the help of real-world datasets. Lastly, the program provides guidance on the best practices for the usage of data science tools and techniques. This includes tips on how to interpret and analyze the results obtained from data science models. In conclusion, 4Achievers' Data Science Training program provides comprehensive guidance on the use of data science tools.
Yes, 4Achievers provides guidance on using data science libraries during the Data Science Training program. 4Achievers program includes sessions that cover topics such as data science libraries and their functions, installation of data science libraries, and how to use them. 4Achievers training also provides hands-on experience with popular data science libraries such as Pandas, Scikit-learn, and NumPy, which can help the participant understand data science concepts better and use these libraries to build projects. 4Achievers instructor will also explain and demonstrate the best practices of using data science libraries and how they can be applied to different scenarios. 4Achievers program also provides resources and practice problems to help the participant gain a deeper understanding of data science libraries and how to use them.
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First touchpoint for customer Initial handling of all customer tickets Track to closure of customer tickets by assisting the responsible teams System software and AWS/Azure infrastructure L1/L2 support Newgen solution / application L1/L2 support Responsib
Experience: 0 to 4 years Qualification:B.SC, B.Tech/BE/MCA Skills in one or more of JavaScript,CSS, Web application framework viz. Sencha EXT JS, JQuery etc., Delphi,C,C++,or Java..net,testing Cloud Administrator-managing Windows based Servers
Developing and deploying new applications on the windows azure PAAS platform using C#, .net core . Participation in the creation and management of databases like SQL server and MySQL Understanding of data storage technology (RDBMS, NO SQL). Manage applica
Experience of Dev Ops technologies, architectures and processes for 3 yrs Cloud Infrastructures Solutions: AWS EC2 ECS, S3 Cloudfront, RDS, Spot Instances, VPC, IAM, Security Groups, ELB etc), GCP, CI/CD Jenkins Containerization: Docker, Kubernetes System
Must have good knowledge of Google Cloud (GCP), Good To Have- AWS and. Azure Cloud automation, with overall cloud computing experience. Good knowledge of Windows Server and IIS (Internet Information Services). Good knowledge of .NET applications (ASP.Net,
Good Knowledge in both Manual Testing and Automation Testing,Strong experience in writing test scenarios and test cases Strong knowledge on Selenium, Appium, Microsoft SQL and Jmeter Adept in functional testing and reporting defects
Design, execute and report software tests, Review business / software requirements and provide inputs. Prepare test cases, test scripts and test data., Execute tests (manual / automated). Report defects and assist in their understanding., Analyse test re
Good Knowledge in both Manual Testing and Automation Testing,Strong experience in writing test scenarios and test cases Strong knowledge on Selenium, Appium, Microsoft SQL and Jmeter Adept in functional testing and reporting defects
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