Data Science Training by Experts

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Data Science - Syllabus, Fees & Duration

MODULE 1

  • The Data Science Process
  • Apply the CRISP-DM process to business applications
  • Wrangle, explore, and analyze a dataset
  • Apply machine learning for prediction
  • Apply statistics for descriptive and inferential understanding
  • Draw conclusions that motivate others to act on your results

MODULE 2

  • Communicating with Stakeholders
  • Implement best practices in sharing your code and written summaries
  • Learn what makes a great data science blog
  • Learn how to create your ideas with the data science community

MODULE 3

  • Software Engineering Practices
  • Write clean, modular, and well-documented code
  • Refactor code for efficiency
  • Create unit tests to test programs
  • Write useful programs in multiple scripts
  • Track actions and results of processes with logging
  • Conduct and receive code reviews

MODULE 4

  • Object Oriented Programming
  • Understand when to use object oriented programming
  • Build and use classes
  • Understand magic methods
  • Write programs that include multiple classes, and follow good code structure
  • Learn how large, modular Python packages, such as pandas and scikit-learn, use object oriented programming
  • Portfolio Exercise: Build your own Python package

MODULE 5

  • Web Development
  • Learn about the components of a web app
  • Build a web application that uses Flask, Plotly, and the Bootstrap framework
  • Portfolio Exercise: Build a data dashboard using a dataset of your choice and deploy it to a web application

MODULE 6

  • ETL Pipelines
  • Understand what ETL pipelines are
  • Access and combine data from CSV, JSON, logs, APIs, and databases
  • Standardize encodings and columns
  • Normalize data and create dummy variables
  • Handle outliers, missing values, and duplicated data
  • Engineer new features by running calculations • Build a SQLite database to store cleaned data

MODULE 7

  • Natural Language Processing
  • Prepare text data for analysis with tokenization, lemmatization, and removing stop words
  • Use scikit-learn to transform and vectorize text data
  • Build features with bag of words and tf-idf
  • Extract features with tools such as named entity recognition and part of speech tagging
  • Build an NLP model to perform sentiment analysis

MODULE 8

  • Machine Learning Pipelines
  • Understand the advantages of using machine learning pipelines to streamline the data preparation and modeling process
  • Chain data transformations and an estimator with scikit- learn’s Pipeline
  • Use feature unions to perform steps in parallel and create more complex workflows
  • Grid search over pipeline to optimize parameters for entire workflow
  • Complete a case study to build a full machine learning pipeline that prepares data and creates a model for a dataset

MODULE 9

  • Experiment Design
  • Understand how to set up an experiment, and the ideas associated with experiments vs. observational studies
  • Defining control and test conditions
  • Choosing control and testing groups

MODULE 10

  • Statistical Concerns of Experimentation
  • Applications of statistics in the real world
  • Establishing key metrics
  • SMART experiments: Specific, Measurable, Actionable, Realistic, Timely

MODULE 11

  • A/B Testing
  • How it works and its limitations
  • Sources of Bias: Novelty and Recency Effects
  • Multiple Comparison Techniques (FDR, Bonferroni, Tukey)
  • Portfolio Exercise: Using a technical screener from Starbucks to analyze the results of an experiment and write up your findings

MODULE 12

  • Introduction to Recommendation Engines
  • Distinguish between common techniques for creating recommendation engines including knowledge based, content based, and collaborative filtering based methods.
  • Implement each of these techniques in python.
  • List business goals associated with recommendation engines, and be able to recognize which of these goals are most easily met with existing recommendation techniques.

MODULE 13

  • Matrix Factorization for Recommendations
  • Understand the pitfalls of traditional methods and pitfalls of measuring the influence of recommendation engines under traditional regression and classification techniques.
  • Create recommendation engines using matrix factorization and FunkSVD
  • Interpret the results of matrix factorization to better understand latent features of customer data
  • Determine common pitfalls of recommendation engines like the cold start problem and difficulties associated with usual tactics for assessing the effectiveness of recommendation engines using usual techniques, and potential solutions.

Download Syllabus - Data Science
Course Fees
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Data Science Jobs in Ahmadi

Enjoy the demand

Find jobs related to Data Science in search engines (Google, Bing, Yahoo) and recruitment websites (monsterindia, placementindia, naukri, jobsNEAR.in, indeed.co.in, shine.com etc.) based in Ahmadi, chennai and europe countries. You can find many jobs for freshers related to the job positions in Ahmadi.

  • Data Scientist
  • Data Analyst
  • Data Engineer
  • Data Storyteller
  • Machine Learning Scientist
  • Machine Learning Engineer
  • Business Intelligence Developer
  • Database Administrator
  • ML Engineer
  • Computer Vision Engineer

Data Science Internship/Course Details

Data Science internship jobs in Ahmadi
Data Science Effectively analyze both organized and unstructured data Create strategies to address company issues. This curriculum prepares you to work in a variety of Data Science professions and earn top-dollar wages. Experts provide immersive online instructor-led seminars. Create data strategies with the help of team members and leaders. This finest Data Science course was built with the needs of businesses in mind when it comes to the field of Data Science. A data scientist is a person who uses a variety of procedures, methods, systems, and algorithms to analyze data to provide actionable insights. Creative thinking, problem-solving skills, curiosity, and a drive to learn about and investigate industry trends and development, as well as teamwork, are among the soft skills required by data scientists. You may learn all of the skills and talents required to become a data scientist by enrolling in the top data science online courses in Ahmadi. The Data Science Process, Communicating with Stakeholders, Software Engineering Practices, Object-Oriented Programming, Web Development, ETL Pipelines, Natural Language Processing, Machine Learning Pipelines, Experiment Design, Statistical Concerns of Experimentation, A/B Testing, and Introduction to Recommendation Engines are some of the topics covered in. You'll have a personal mentor who will keep track of your development.

List of All Courses & Internship by TechnoMaster

Success Stories

The enviable salary packages and track record of our previous students are the proof of our excellence. Please go through our students' reviews about our training methods and faculty and compare it to the recorded video classes that most of the other institutes offer. See for yourself how TechnoMaster is truly unique.

List of Training Institutes / Companies in Ahmadi

  • INDIAN:DRIVINGSCHOOLINKUWAIT | Location details: Mahboula block 2 Street 206 Al Ahmadi, 13006, Kuwait | Classification: Driving school, Driving school | Visit Online: drivingclasskw.com | Contact Number (Helpline): +965 9899 9479
  • جامعةالتقنيةوالعلومالتطبيقية(الكليةالتقنيةبإبراء) | Location details: Al Yahmadi Ibra, North Al Sharqiya Ibra OM, 400, Oman | Classification: Government college, Government college | Visit Online: ict.edu.om | Contact Number (Helpline): +968 25 587800
  • INDIAN:DRIVINGSCHOOLINKUWAIT | Location details: Mahboula block 2 Street 206 Al Ahmadi, 13006, Kuwait | Classification: Driving school, Driving school | Visit Online: drivingclasskw.com | Contact Number (Helpline): +965 9899 9479
  • HSEInductionCenter | Location details: 33Q4+24G, Ahmadi, Kuwait | Classification: Training centre, Training centre | Visit Online: kockw.com | Contact Number (Helpline):
  • LondonChocolateAhmadi-PetroleumTrainingCenter | Location details: Mid 16th St، Kuwait City, Kuwait | Classification: Shopping mall, Shopping mall | Visit Online: londonchoco.com | Contact Number (Helpline): +965 2381 3996
  • KOCTrainingArea | Location details: 2X2G+97M, Ahmadi, Kuwait | Classification: Training centre, Training centre | Visit Online: | Contact Number (Helpline):
  • PetroleumResearchCenter | Location details: 33WM+6R4, Ahmadi, Kuwait | Classification: Research institute, Research institute | Visit Online: | Contact Number (Helpline): +965 2398 7672
  • اكاديميةالخيالحلبةوميدانتدريبركوبخيلHorsridingTrainingCamp | Location details: W4MG+XCJ, Ahmadi, Kuwait | Classification: Gym, Gym | Visit Online: | Contact Number (Helpline): +965 505 63020
  • UniversityOfTechnologyAndAppliedScience,Ibra | Location details: PO Box 327 Al Yahmadi Ibra, North Al Sharqiya, PC 400, Oman | Classification: Government college, Government college | Visit Online: ict.edu.om | Contact Number (Helpline): +968 25 587800
  • WataniyaEnvironmentalServiceCo.K.S.C.C-BranchOffice | Location details: 34J4+VJJ, Ahmadi, Kuwait | Classification: Consultant, Consultant | Visit Online: | Contact Number (Helpline): +965 6007 3890
  • UniversityOfTechnologyAndAppliedScience,Ibra | Location details: PO Box 327 Al Yahmadi Ibra, North Al Sharqiya, PC 400, Oman | Classification: Government college, Government college | Visit Online: ict.edu.om | Contact Number (Helpline): +968 25 587800
  • Al-WassenElectronicsCo. | Location details: 33MM+MC6, Ahmadi, Kuwait | Classification: Computer networking center, Computer networking center | Visit Online: alwassen.com | Contact Number (Helpline):
  • INDIAN:DRIVINGSCHOOLINKUWAIT | Location details: Mahboula block 2 Street 206 Al Ahmadi, 13006, Kuwait | Classification: Driving school, Driving school | Visit Online: drivingclasskw.com | Contact Number (Helpline): +965 9899 9479
  • LondonChocolateAhmadi-PetroleumTrainingCenter | Location details: Mid 16th St، Kuwait City, Kuwait | Classification: Shopping mall, Shopping mall | Visit Online: londonchoco.com | Contact Number (Helpline): +965 2381 3996
  • TitaniumSharkGym | Location details: Block 1 street 10 bldg 124 Mahboula, Al Ahmadi, Kuwait, 63000, Kuwait | Classification: Gym, Gym | Visit Online: | Contact Number (Helpline): +965 6090 4631
  • KPCTrainingWorkshop | Location details: 33RJ+6H2, Ahmadi, Kuwait | Classification: Machine workshop, Machine workshop | Visit Online: | Contact Number (Helpline):
 courses in Ahmadi
One of the earliest scholarly works that focuses on the oil industry's impact on the Arab Gulf and its effect on population and distribution patterns is by labor experts Ian Seccombe and Richard Lawless. Despite this enormous resource on Kuwait’s history, it had no substantial sources on either the KOC or Ahmadi both of which played key roles in the making of the modern nation of Kuwait. . 6 Despite its excavation of a new scholarly arena regarding oil and settlement patterns, the study remains restricted by its policy-oriented labor specialization causing an unfortunate lack in any formal or spatial analysis. Geographer Kaveh Ehsani7 and art historian Mark Crinson,8 have both contributed significantly regarding the Anglo-Persian Oil Company town of Abadan in Iran and its modernizing role. In the case of Kuwait City, in 1964 Saba Shiber published a detailed critical account of its urbanization as the old vernacular town was razed for a modern metropolis. The primary sources relied upon fall under two major categories: archival and ethnographic. Uncovering the urban history of Ahmadi in the field and on the ground both in Kuwait and at the KOC headquarters themselves proved to be quite challenging. The discovery of oil in Kuwait has decisively impacted the political, economic, social, cultural and built landscape. 5 However these perspectives fail to acknowledge that in oil-fueled entities urban modernity first occurred in oil company towns with imperial powers, multi-national corporations and foreign architects playing an influential role in their architectural and urban development.

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