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Learn the fundamental data science concepts. Join today to become a competent data science expert.

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Data Science & AI

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  • Data Science is a legit field of study that blends domain expertise, programming skills, and in-depth information on mathematics and statistics to extract meaningful insights from data. It is one kind of a process that implements machine learning algorithms for numbers, text, images, video, and audio, to come up with artificial intelligence (AI) systems to perform numerous tasks that ordinarily require human intelligence. In the present scenario, it holds a lot of importance and various organizations are also making the best use of it. If you also want to turn into a knowledgeable Data Scientist, you must enrol yourself in the Data Science Online Course in Dubai to kick-start your career in this direction.

Data Science Online Training in Dubai

About-Us-Course

  • You might consider this specific course very complex, but our Data Science Online Training in Dubai will assist you to prepare for numerous cloud certifications so that your core concept regarding this advancement.
  • Here are some of the topics, that you will cover in this course:
    • Right at the beginning of the course, you will first understand its basic fundamental information.

      You will get to know about data structure and data manipulation in detail.

      You will also know about supervised and unsupervised learning models such as linear regression, logistic regression, clustering, dimensionality reduction, K-NN, and pipeline.

      Our trainers will therefore help you thoroughly to know the process of executing scientific and technical computing utilizing the SciPy package and its sub-packages such as Integrate, Optimize, Statistics, IO, and Weave.

      You will also gain expertise in mathematical computing using the NumPy and Scikit-Learn packages.

      Post the completion of the Data Science Online Course in Dubai, you will examine data utilizing Tableau and become proficient in developing interactive dashboards respectively.

  • There's no doubt that Data Scientists are paid well, still, there's a scarcity of skilled Data Scientists. And in this case, enrolling in Data Science Online Training in Dubai will be best for your career.
  • Refer to the points mentioned below to know the salary of fresher Data Scientists, and experienced Data Scientists.
    • A beginner Data Scientist earns around Rs. 5,71,493 per year.

      Likewise, an experienced Data Scientist holding more than 9-10 years of experience in this field makes around Rs. 18,40,360 or even more.

      Well, the salary structure is generally based upon the overall total experience of the candidate, skills, information, and trends they have.

      By obtaining in-depth information about data science implementation, and its latest updates, your salary structure will increase.

      Withholding Data Science Online Certification in Dubai, you will end up earning a bit higher salary than normal employees.

  • Our job-oriented Data Science Online Training in Dubai will cover every necessary data science aspect that will make you industry-ready to imply those methodologies practically.
  • Also, our Data Science trainers will guide you consecutively to earn certifications and get placed in leading industries worldwide.
    • You will get the choice to select from numerous job opportunities.

      You will acquire adequate skills and information to pass the certification exam.

      By enrolling in our Data Science Online Course in Dubai, you will turn into a knowledgeable Data Scientist.

      Our training program will provide you with information right from scratch that will eventually strengthen your core information.

  • Over the past few years, the field of data science has grabbed the immense limelight. One of the main reasons behind the Data Science Online Certification in Dubai’s popularity is that it assures various organizations to efficiently process and elucidate data.
  • Refer to the points mentioned below to know other highlighting reasons to learn Data Science.
    • Numerous job opportunities

      Higher salary structure

      Enough learning opportunities

      Vibrant scope

      It's one of the fastest-growing fields

      It’s been implemented in a wide range of industries

  • A Data Scientist is accountable to perform several tasks. Well, they are the ones who are responsible for executing data mining procedures, data examining and several other processes to make the best use of data.
  • Likewise, to execute these procedures, you need to know the exact skills, and by enrolling in our Data Science Online Training in Dubai, you will analyse every role in a much easier manner.
    • While working as a Data Scientist, you will have to accumulate data, identify resources, and analyse and manipulate data as well.

      You will also have to analyse huge volumes of data, both structured and unstructured, that come up with effective solutions and methodologies to business problems, find trends and patterns, conjoin numerous algorithms and modules, etc.

      You might also have to display data utilizing various data visualization techniques and tools.

      You will also have to make the best utilization of statistical programming languages like R or Python.

      You have to perform data analysis, data congestion, data filtration, data mapping, etc.

      You will also have to utilize big data tools like Hadoop, Hive, Map Reduce, etc.

  • Well, various top-notch organizations are looking for skilled and experienced SAFe Agilist who can perform numerous tasks smoothly. So, enrolling in the Data Science Online Course in Dubai will be beneficial for you in getting settled in a well-established company.
    • Accenture, AWS, Genpact, etc are some of the well-known companies hiring skilled Data Scientist.

      By enrolling yourself on the Data Science Online Certification in Dubai, you will imbibe detailed information regarding its business procedures, and models.

      By knowing each side of Data Science, you will surely get into a well-established company.

  • Croma Campus is one of the well-known educational foundations that has been providing Data Science Online Training in Dubai for a very long time and has been receiving positive feedback from its passed candidates.
  • So, if you also want to know how data mining or Data Scientists work, enrol yourself in the Data Science Online Course in Dubai to uplift your career graph.
    • Here, you will receive detailed information regarding its related course as well.

      Croma Campus will offer you placement assistance.

      Well, right from the beginning of the Data Science Online Certification in Dubai, our trainers will give you suggestive tips to clear the interview process so that you can get placed in a well-established company.

Why should you get started with the Data Science Course?

Not just learning –

we train you to get hired.

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CURRICULUM & PROJECTS

Data Science Training Program

    NA

    • Introduction To Python
      • Installation and Working with Python
      • Understanding Python variables
      • Python basic Operators
      • Understanding the Python blocks.
      • Version Control with Git & GitHub
    • Python Keyword and Identiers
      • Python Comments, Multiline Comments.
      • Python Indentation
      • Understating the concepts of Operators
    • Introduction To Variables
      • Variables, expression condition and function
      • Global and Local Variables in Python
      • Packing and Unpacking Arguments
      • Type Casting in Python
      • Byte objects vs. string in Python
      • Variable Scope
    • Python Data Type
      • Declaring and using Numeric data types
      • Using string data type and string operations
      • Understanding Non-numeric data types
      • Understanding the concept of Casting and Boolean.
      • Strings
      • List
      • Tuples
      • Dictionary
      • Sets
    • Control Structure & Flow
      • Statements if, else, elif
      • How to use nested IF and Else in Python
      • Loops
      • Loops and Control Statements.
      • Jumping Statements Break, Continue, pass
      • Looping techniques in Python
      • How to use Range function in Loop
      • Programs for printing Patterns in Python
      • How to use if and else with Loop
      • Use of Switch Function in Loop
      • Elegant way of Python Iteration
      • Generator in Python
      • How to use nested Loop in Python
      • Use If and Else in for and While Loop
      • Examples of Looping with Break and Continue Statement
      • How to use IN or NOT IN keyword in Python Loop.
    • Python Function, Modules and Packages
      • Python Syntax
      • Function Call
      • Return Statement
      • Arguments in a function Required, Default, Positional, Variable-length
      • Write an Empty Function in Python pass statement.
      • Lamda/ Anonymous Function
      • *args and **kwargs
      • Help function in Python
      • Scope and Life Time of Variable in Python Function
      • Nested Loop in Python Function
      • Recursive Function and Its Advantage and Disadvantage
      • Organizing python codes using functions
      • Organizing python projects into modules
      • Importing own module as well as external modules
      • Understanding Packages
      • Random functions in python
      • Programming using functions, modules & external packages
      • Map, Filter and Reduce function with Lambda Function
      • More example of Python Function
    • List
      • What is List.
      • List Creation
      • List Length
      • List Append
      • List Insert
      • List Remove
      • List Append & Extend using + and Keyword
      • List Delete
      • List related Keyword in Python
      • List Revers
      • List Sorting
      • List having Multiple Reference
      • String Split to create a List
      • List Indexing
      • List Slicing
      • List count and Looping
      • List Comprehension and Nested Comprehension
    • Tuple
      • What is Tuple
      • Tuple Creation
      • Accessing Elements in Tuple
      • Changing a Tuple
      • Tuple Deletion
      • Tuple Count
      • Tuple Index
      • Tuple Membership
      • TupleBuilt in Function (Length, Sort)
    • Dictionary
      • Dict Creation
      • Dict Access (Accessing Dict Values)
      • Dict Get Method
      • Dict Add or Modify Elements
      • Dict Copy
      • Dict From Keys.
      • Dict Items
      • Dict Keys (Updating, Removing and Iterating)
      • Dict Values
      • Dict Comprehension
      • Default Dictionaries
      • Ordered Dictionaries
      • Looping Dictionaries
      • Dict useful methods (Pop, Pop Item, Str , Update etc.)
    • Sets
      • What is Set
      • Set Creation
      • Add element to a Set
      • Remove elements from a Set
      • PythonSet Operations
      • Frozen Sets
    • Strings
      • What is Set
      • Set Creation
      • Add element to a Set
      • Remove elements from a Set
      • PythonSet Operations
    • Python Exception Handling
      • Python Errors and Built-in-Exceptions
      • Exception handing Try, Except and Finally
      • Catching Exceptions in Python
      • Catching Specic Exception in Python
      • Raising Exception
      • Try and Finally
    • Python File Handling
      • Opening a File
      • Python File Modes
      • Closing File
      • Writing to a File
      • Reading from a File
      • Renaming and Deleting Files in Python
      • Python Directory and File Management
      • List Directories and Files
      • Making New Directory
      • Changing Directory
    • Python Database Interaction
      • Basic SQL, DDL and DML commands
      • SQL Database connection using
      • Creating and searching tables
      • Reading and Storing cong information on database
      • Programming using database connections
    • Reading an excel
      • Working With Excel
      • Reading an excel le using Python
      • Writing to an excel sheet using Python
      • Python| Reading an excel le
      • Python | Writing an excel le
      • Adjusting Rows and Column using Python
      • ArithmeticOperation in Excel le.
      • Play with Workbook, Sheets and Cells in Excel using Python
      • Creating and Removing Sheets
      • Formatting the Excel File Data
      • More example of Python Function
    • Complete Understanding of OS Module of Python
      • Check Dirs. (exist or not)
      • How to split path and extension
      • How to get user prole detail
      • Get the path of Desktop, Documents, Downloads etc.
      • Handle the File System Organization using OS
      • How to get any les and folders details using OS
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    NA

    • Data Analysis and Visualization using Pandas.
      • Read data from Excel File using Pandas More Plotting, Date Time Indexing and writing to les
      • How to get record specic records Using Pandas Adding & Resetting Columns, Mapping with function
      • Using the Excel File class to read multiple sheets More Mapping, Filling Nonvalues
      • Exploring the Data Plotting, Correlations, and Histograms
      • Getting statistical information about the data Analysis Concepts, Handle the None Values
      • Reading les with no header and skipping records Cumulative Sums and Value Counts, Ranking etc
      • Reading a subset of columns Data Maintenance, Adding/Removing Cols and Rows
      • Applying formulas on the columns Basic Grouping, Concepts of Aggre gate Function
      • Complete Understanding of Pivot Table Data Slicing using iLoc and Loc property (Setting Indices)
      • Under sting the Properties of Pivot Table in Pandas Advanced Reading CSVs/HTML, Binning, Categorical Data
      • Exporting the results to Excel Joins
      • Python | Pandas Data Frame Inner Join
      • Under sting the properties of Data Frame Left Join (Left Outer Join)
      • Indexing and Selecting Data with Pandas Right Join (Right Outer Join)
      • Pandas | Merging, Joining and Concatenating Full Join (Full Outer Join)
      • Pandas | Find Missing Data and Fill and Drop NA Appending Data Frame and Data
      • Pandas | How to Group Data How to apply Lambda / Function on Data Frame
      • Other Very Useful concepts of Pandas in Python Data Time Property in Pandas (More and More)
    • Data Analysis and Visualization using NumPy
      • Introduction to NumPy Numerical Python
      • Importing NumPy and Its Properties
      • NumPy Arrays
      • Creating an Array from a CSV
      • Operations an Array from a CSV
      • Operations with NumPy Arrays
      • Two-Dimensional Array
      • Selecting Elements from 1-D Array
      • Selecting Elements from 2-D Array
      • Logical Operation with Arrays
      • Indexing NumPy elements using conditionals
      • NumPys Mean and Axis
      • NumPys Mode, Median and Sum Function
      • NumPys Sort Function and More
    • Data Analysis and Visualization using MatPlotLib
      • Bar Chart using Python MatPlotLib
      • Column Chart using Python MatPlotLib
      • Pie Chart using Python MatPlotLib
      • Area Chart using Python MatPlotLib
      • Scatter Plot Chart using Python MatPlotLib
      • Play with Charts Properties Using MatPlotLib
      • Export the Chart as Image
      • Understanding plt. subplots () notation
      • Legend Alignment of Chart using MatPlotLib
      • Create Charts as Image
      • Other Useful Properties of Charts.
      • Complete Understanding of Histograms
      • Plotting Different Charts, Labels, and Labels Alignment etc.
    • Introduction to Data Visualization with Seaborn
      • Introduction to Seaborn
      • Making a scatter plot with lists
      • Making a count plot with a list
      • Using Pandas with seaborn
      • Tidy vs Untidy data
      • Making a count plot with a Dataframe
      • Adding a third variable with hue
      • Hue and scattera plots
      • Hue and count plots
      • Visualizing Two Quantitative Variables
      • Visualizing a Categorical and a Quantitative Variable
      • Customizing Seaborn Plots
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    NA

    • Foundation for AI: Learn traditional ML models, evaluation, and workflows.
      • Introduction to ML, AI, and Deep Learning
      • Types of ML (Supervised, Unsupervised, Reinforcement)
      • ML Pipeline: Data Cleaning, Feature Engineering
      • Common ML Algorithms: Linear, Logistic, DT, RF, SVM, KNN
      • Model Evaluation: Accuracy, Precision, Recall, F1, ROC-AUC
      • Overfitting, Underfitting, Cross-Validation
      • Hands-on Project: Titanic Dataset (or similar)
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    NA

    • Understand the inner workings of neural networks and train them with Keras.
      • Introduction to Neural Networks & Deep Learning
      • Activation Functions (ReLU, Sigmoid, Tanh)
      • Feedforward Neural Network
      • Backpropagation & Gradient Descent
      • Learning Rate, Schedulers & Optimizers (SGD, Adam, RMSProp)
      • Softmax, Cross-Entropy Loss
      • Keras Basics: Sequential API & Functional API
      • Fully Connected Layer Forward/Backward Pass
      • Regularization Dropout, Batch Normalization
      • Data Preprocessing & Data Augmentation
      • Weight Initialization Strategies
      • Babysitting Learning: Overfit detection, TensorBoard Monitoring
      • Hands-on: MLP on MNIST / Tabular data (e.g. HR Analytics)
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    NA

    • Master CNNs, object detection, segmentation, and deployment.
      • Basics of Images, Image Preprocessing
      • Convolution: 2D Conv, Forward & Backward
      • Pooling, Padding, Stride, Transposed Conv
      • CNN Architectures: LeNet, AlexNet, VGG, ResNet
      • GPU vs CPU for DL
      • Transfer Learning: Inception, MobileNet, fine-tuning
      • Semantic Segmentation using UNet
      • Object Detection YOLO, SSD, Region Proposal
      • Bounding Box Regressor
      • Siamese Networks for Similarity Search
      • Hands-on:
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    NA

    • Train text models from scratch and with BERT.
      • Introduction to NLP and Use Cases
      • Preprocessing: Tokenization, Lemmatization, Stopwords, Normalization
      • Feature Extraction: BOW, TF-IDF, N-Grams
      • Word Embeddings: Word2Vec, GloVe, Dense Vectors
      • POS Tagging, Named Entity Recognition
      • RNN, LSTM Forward Pass and BPTT
      • Advanced LSTM Applications + Architectures
      • Attention Mechanism + Encoder-Decoder
      • Transformers, BERT, Hugging Face Pipelines
      • NLP Evaluation Metrics: BLEU, ROUGE
      • Hands-on:
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    NA

    • Take models from notebooks to real-world applications.
      • Saving & Loading Models (Pickle, Joblib, Keras)
      • Flask vs FastAPI Serving ML models
      • Streamlit/Gradio for Web Apps
      • Hosting Models on Hugging Face Spaces, Streamlit Cloud
      • MLflow Intro Model Tracking & Versioning
      • Hands-on:
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    NA

    • Build, evaluate, and deploy a mini AI project end-to-end.
      • Project Selection: Tabular, CV, or NLP
      • Data Collection/Exploration
      • Preprocessing + Feature Engineering
      • Model Training & Tuning
      • Evaluation & Interpretation
      • App Creation (Streamlit/Gradio)
      • Deployment + Final Presentation/Submission
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Prepare & Practice for real-life job interviews by joining the Mock Interviews drive at Croma Campus and learn to perform with confidence with our expert team.Not sure of Interview environments? Don’t worry, our team will familiarize you and help you in giving your best shot even under heavy pressures.Our Mock Interviews are conducted by trailblazing industry-experts having years of experience and they will surely help you to improve your chances of getting hired in real.
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Well, no it’s not a very costly course, but here, you have the option to pay in two instalments.

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