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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
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Data Science Jobs in Muharraq

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 Muharraq, chennai and europe countries. You can find many jobs for freshers related to the job positions in Muharraq.

  • 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 Muharraq
Data Science Cleaning and validating data to ensure that it is accurate and consistent. Data Science provides a diverse set of tools for analyzing data from a range of sources, including financial records, multimedia files, marketing forms, sensors, and text files. To succeed as a data scientist, you must, nevertheless, make a particular effort to apply soft skills. Today's Data Scientists must possess a wide range of abilities, including the ability to work with large amounts of data, parse that data, and translate it into an easily comprehensible format from which business insights may be drawn. 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. Exercises, tasks, and projects that are completed in real-time 24 hours a day, 7 days a week, A large network of like-minded newbies, an industry-recognized intellipaat credential, and individualized employment support Several data scientist responsibilities are listed below. Experts provide immersive online instructor-led seminars. 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 may learn all of the skills and talents required to become a data scientist by enrolling in the top data science online courses in Muharraq. There are numerous reasons why you should take this course.

List of All Courses & Internship by TechnoMaster

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List of Training Institutes / Companies in Muharraq

  • Expeditors | Location details: Door 1, Gate 18 GLS Compound, Muharraq Muharraq, Manama, Bahrain | Classification: Freight Forwarding Service, Freight Forwarding Service | Visit Online: expeditors.com | Contact Number (Helpline): +973 1753 2288
  • A2ZAdvertisingAndPublicityWLL | Location details: Rd No 1615, Muharraq, Bahrain | Classification: Advertising agency, Advertising agency | Visit Online: a2zadsbahrain.com | Contact Number (Helpline): +973 3433 9903
  • ShopAndShip | Location details: 3 & 4 Gate 18, GLS Compound، Rayya Hwy, Muharraq, Bahrain | Classification: Delivery Company, Delivery Company | Visit Online: shopandship.com | Contact Number (Helpline): +973 1733 0434
  • MaarejSystemsDevelopment | Location details: Building 588, Rd No 1223, Muharraq, Bahrain | Classification: Software company, Software company | Visit Online: maarejsys.com | Contact Number (Helpline): +973 3402 6833
  • MichaelKors | Location details: Bahrain International Airport, Rd No 2403, Muharraq, Bahrain | Classification: Fashion accessories shop, Fashion accessories shop | Visit Online: locations.michaelkors.com | Contact Number (Helpline): +973 1772 3100
  • AtyafESolutionsCo.W.L.L | Location details: Building 453, Office No. 23، Rd No 711, Muharraq, Bahrain | Classification: Software company, Software company | Visit Online: alnadeem.com | Contact Number (Helpline): +973 1787 7900
  • HertzCarRental | Location details: MANAMA، Muharraq, Bahrain | Classification: Car rental company, Car rental company | Visit Online: | Contact Number (Helpline): +973 1713 8914
  • Boots | Location details: Seef Mall Muharraq, Bahrain | Classification: Pharmacy, Pharmacy | Visit Online: me.boots.com | Contact Number (Helpline): +973 1711 0347
  • SixtRentACar-BahrainIntl.Airport | Location details: Arrival hall, Bahrain International Airport, Muharraq, 199, Bahrain | Classification: Car rental company, Car rental company | Visit Online: sixt.global | Contact Number (Helpline): +973 1713 8920
  • Bath&BodyWorks | Location details: Seef Mall Muharraq, Bahrain | Classification: Beauty supply store, Beauty supply store | Visit Online: bathandbodyworks.com.bh | Contact Number (Helpline): +973 1749 5801
 courses in Muharraq
a . This had a profound impact at the tradition and historical past of the u . This posed a complexity in correlating texts and maps for reconstructing the anciental beyond of the city. Muharraq become Bahrain‟s capital withinside the nineteenth Century and nonetheless has a good deal of the attraction of an vintage-international Arab town, with its low-upward push homes, slender streets and tiny alleyways, and nice anciental homes with their conventional Arab-Gulf fashion of architecture. Present day Muharraq Island become recognised to the Greeks as Aradous and become thereafter generally referred to as Arad and Muharraq was once a part of Arad. . At that time, Bahrain become ruled with the aid of using the Seleucid Greeks, an occasion which has been recorded (Larsen, 1984). 2), may be imagined as a drop of sweat beneath the wrist (Ward, 1983). 2. The records consequently compiled from anciental money owed of guests and maps created withinside the beyond, offers perception into the urbanization sample withinside the beyond and the numerous factors of the city cloth and the tribes which settled there.

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