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
10000+
20+
50+
25+

Data Science Jobs in Agra

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

  • 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 Agra
Data Science 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. A data scientist is a person who uses a variety of procedures, methods, systems, and algorithms to analyze data to provide actionable insights. Effectively analyze both organized and unstructured data Create strategies to address company issues. There are numerous reasons why you should take this course. . Cleaning and validating data to ensure that it is accurate and consistent. Identify and collect data from data sources. 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. This finest Data Science course was built with the needs of businesses in mind when it comes to the field of Data Science. Create data strategies with the help of team members and leaders.

List of All Courses & Internship by TechnoMaster

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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 Agra

  • PostOffice | Location details: Sector 10, Avas Vikas Colony, Sikandra, Agra, Uttar Pradesh 282007, India | Classification: Post office, Post office | Visit Online: indiapost.gov.in | Contact Number (Helpline): +91 1800 11 2011
  • DainikJagranOfficeKatihar | Location details: 3rd Floor, Aditya Complex, Mirchaibari Chowk, near Hanuman Mandir, Katihar, Bihar 854105, India | Classification: Newspaper publisher, Newspaper publisher | Visit Online: jagran.com | Contact Number (Helpline):
  • WeddingPlannerAndDestinationWeddingInBhilai-Raipur|HumsafarWeddings | Location details: In Front of Kool Beb's, 2nd Floor, 18/1, Agrasen Chowk, C.G, Nehru Nagar, Chhattisgarh 490020, India | Classification: Wedding planner, Wedding planner | Visit Online: humsafar.co | Contact Number (Helpline): +91 83053 77774
  • CentralPublicWorksDepartment | Location details: Sanjay Palace, Sanjay Place, Madhu Nagar, Agra, Uttar Pradesh 282002, India | Classification: Public works department, Public works department | Visit Online: cpwd.gov.in | Contact Number (Helpline): +91 562 285 0556
  • SofconIndiaPvtLtd | Location details: 36, JawaharLal Nehru Road, Near Tejas Microclinic, opp. IDBI Bank, Prayagraj, Uttar Pradesh 211002, India | Classification: Training centre , Training centre | Visit Online: sofcontraining.com | Contact Number (Helpline): +91 77040 03025
  • CPIMMURSHIDABADOFFICE | Location details: H.no, 33/1A, KN Rd, Khagra, Berhampore, West Bengal 742101, India | Classification: Political party, Political party | Visit Online: murshidabad.gov.in | Contact Number (Helpline): +91 3482 256 032
  • StateBankOfIndiaAgra | Location details: E-773, C Block Road, near SBI, E Block, Ghatwasan, Kamla Nagar, Agra, Uttar Pradesh 282005, India | Classification: Bank, Bank | Visit Online: | Contact Number (Helpline):
  • LaptopRepairFirozabad | Location details: 7, Agra Rd, Opp Trauma Centre, Jain Mandir Market, Mahaveer Nagar, Uttar Pradesh 283203, India | Classification: Computer repair service, Computer repair service | Visit Online: durgainfotech.co.in | Contact Number (Helpline):
  • PoliceStation | Location details: 2264/1, Raikot Rd, Labor Nagar, Khaal Mohalla, Jagraon, Punjab 142026, India | Classification: Traffic police station, Traffic police station | Visit Online: ludhianaruralpolice.in | Contact Number (Helpline):
  • AshokKrSinha(postOffice) | Location details: Front of agrasan bhawa. Ward No. 37, Binodpur, Katihar, Bihar 854105, India | Classification: Home builder consultant architect civil engineering construction structured building builders, Home builder consultant architect civil engineering construction structured building builders | Visit Online: | Contact Number (Helpline):
  • TrackonCouriersPrivateLimited | Location details: H.O. : 239 Bypass Road Infront of Shree Talkies, Indra Puri, New Agra Colony, Agra, Uttar Pradesh 282004, India | Classification: Courier service, Courier service | Visit Online: trackoncouriers.com | Contact Number (Helpline):
  • SuryaGraphics(DigitalPrint/OffsetPrint/Signages/OutDoorAdd)) | Location details: No: 17, New Agraharam Street, Kosapet, Vellore, Tamil Nadu 632001, India | Classification: Digital printing service, Digital printing service | Visit Online: suryagraphics.com | Contact Number (Helpline):
  • KheriaModePostOffice-IndiaPost | Location details: SH 39, Nai Basti, Syam Nagar, Arjun Nagar, Agra, Uttar Pradesh 282001, India | Classification: Post office, Post office | Visit Online: indiapost.gov.in | Contact Number (Helpline): +91 1800 11 2011
  • TecZAMarketResearchServicesPvt.Ltd. | Location details: 2nd Floor, Venkataswamy Reddy Building, NGR Layout, Roopena Agrahara, Bommanahalli, Bengaluru, Karnataka 560068, India | Classification: Market researcher, Market researcher | Visit Online: | Contact Number (Helpline): +91 80 6050 5595
  • AnandMarketing | Location details: Shop No 1, Satlok Plaza, Beside Hotel Pritam, Fawar Chowk, Central Ave, Agrasen Square, Gandhibagh, Nagpur, Maharashtra 440002, India | Classification: Marketing, Marketing | Visit Online: +91 712 261 1597 | Contact Number (Helpline):
  • DeepakAgrawal | Location details: Golpura Rd, Subhash Nagar, Bharatpur, Rajasthan 321001, India | Classification: Employment center, Employment center | Visit Online: business.site | Contact Number (Helpline): +91 96803 07990
 courses in Agra
He became defeated via way of means of Sher Shah Suri in 1540 and the citadelress became below the Suris until 1555. After this, Akbar, Jahangir, Shah Jahan, and Aurangzeb dominated from right here. Then Jahangir and Shah Jahan constructed many different systems in the citadelress. The draw bridge can flip to ninety diploma among outer and internal gates. He defeated Tardi Beg Khan the chief of Mughal forces however he became defeated withinside the 2nd warfare of Panipat via way of means of Akbar. Shah Jahan has additionally constructed white marble palaces and to try this he destroyed a number of the monuments. He did not bounce as the pony died whilst leaping and Amar Singh became positioned to death. At that point Jayapala became the king of Agra. The partitions of the citadelress are 70 ft high. Agra below Lodis Sikandar Lodi made Agra his capital in 1506 and after him his son Ibrahim Lodi dominated the metropolis.

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