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Learn the fundamental data science concepts. Join today to become a competent data science expert.
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145 Hrs.
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we train you to get hired.
- To begin with, Data Science refers to the practice of studying the data to extract meaningful insights for business. Furthermore, it consists of domain expertise, programming skills, and knowledge of mathematics and statistics to extract meaningful insights from data. The Data Science Online Course in Qatar will help you understand the Data Science process. Moreover, it will help you understand Cloud concepts & applications in Data Science. You will get to know about Database concepts and statistics fundamentals as needed in Data Science. Above all, you will get to learn visualizations for data mining and presentation, and will provide you with an overview of Statistical Learning. Let's move further and have a look at the course objectives.
Data Science Online Training in Qatar
- This Data Science Online Course in Qatar provides you with the entire toolbox you need to become a data scientist. It helps you add weight to your resume and teaches you various in-demand data science skills like Statistical analysis, and Python programming. Enrolling in this Data Science Online Course in Qatar helps you impress interviewers by showing an understanding of the data science field. Furthermore, you will learn how to pre-process data and understand the mathematics behind Machine Learning. Data Science Online Training in Qatar will teach you coding in Python and help you learn how to use it for statistical analysis. Moreover, you will be able to perform linear and logistic regressions in Python. Above all, this course will help you carry out cluster and factor analysis. Apart from these, given below are some of the concepts you will learn after doing Data Science Online Training in Qatar.
Successfully performing all steps in a complex Data Science project.
Apply the Cumulative Accuracy Profile (CAP) to assess models.
It will help you derive business insights from the coefficients of logistic regression.
Apply three levels of model maintenance to prevent model deterioration.
Use SQL Server Integration Services (SSIS) to upload data into a database.
It will teach you how to deal with text Qualifier errors in RAW data.
You will be able to present Data Science projects to stakeholders.
- The average starting salary for Data Scientist in India is around 4.0 Lakhs per annum or 33.3k per month. Having more than 1 year of experience as a Data Scientist can provide you with an average of Rs. 5,71,493 annually. Meanwhile, Data Scientists with 1 to 4 years of experience earn an average of Rs. 8,00,750 per annum. Furthermore, skilled and experienced professionals can earn high as 25.0 Lakhs per year. However, these are just average figures and your salary depends on your skillsets and how well you perform in your interview. Here are some of the average salaries of professionals with data science skills in India.
Data Scientists earn an average of 10.0 Lakhs INR.
Data architects earn an average of 23.5 Lakhs INR.
Machine Learning engineers earn an average of 7.0 Lakhs INR.
Business Intelligence Developers earn an average of 6.0 Lakhs INR.
Database Engineers earn an average of 6.0 Lakhs INR.
Data Analysts earn an average of 4.3 Lakhs INR.
Data engineers earn an average of 8.0 Lakhs INR.
- Data Science continues to be one of the most promising and in-demand careers in the IT domain. It offers rewarding and lucrative job opportunities as it is a highly in-demand job role in the market because of the increased use of data in every sector. It is a good career with tremendous opportunities for advancement in the future. It is already in high demand and it offers competitive salaries with numerous perks. Many institutes provide Data Science Online Courses in Qatar and one can enroll in them to start a career in this domain. Here are some of the job opportunities you can explore after learning Data Science.
Data Analyst
Data Engineers
Database Administrator
Machine Learning Engineer
Data Scientist
Data Architect
Statistician
Business Analyst
Data and Analytics Manager
- Data Scientists are responsible for extracting data from multiple sources. After that, these professionals use machine learning tools to organize, process, clean, validate, and analyze the data for information and patterns. Furthermore, they need to develop prediction systems, present the data in a clear manner, and propose solutions and strategies. Many institutes provide Data Science Online Training in Qatar and one can enroll in them to start a career as a Data Scientist.
Identifying valuable data sources and automating collection processes
Undertaking preprocessing of structured and unstructured data
Analyzing large amounts of information to discover trends and patterns
Building predictive models and machine-learning algorithms
Combining models through ensemble modeling
Presenting information using data visualization techniques
Proposing solutions and strategies to business challenges
Collaborating with engineering and product development teams
- Data Science is the Career of Tomorrow as industries are becoming data-driven and new innovations are being made every day. In addition, this technology has become dynamic and with more and more people interacting with the internet, more data is being generated. Therefore, industries require skilled professionals in data science that can assist them in making smarter decisions and creating better products. Thus, generating many promising career opportunities in it. Data Science Online Training in Qatar teaches you all aspects of this technology and makes you capable enough of starting a career in data science. Apart from these, given below are some of the reasons why you should enroll in the Data Science Online Course in Qatar.
It is a necessary and demanding skill in the 21st century.
Offers you an abundance of career opportunities in many sectors.
It is a lucrative career where there is an abundance of positions.
This is a versatile domain and there are a variety of applications of data science.
Makes you eligible for positions across various domains and industries.
- Data Science facilitates efficient and data-driven decision-making as it relies on mathematical and statistical formulas to extract data and make sense of it. It helps a company in making business decisions and helps leaders during complex business scenarios. Data science helps in identifying business opportunities and allows a company to forecast future market conditions. This technology helps a business in making fundamental changes and preparing for adversities. Data Science is useful in automating recruitment and different processes and makes it imperative for organizations to recruit data scientists, rendering the benefits of employing them. Above all, it reduces risks by allowing a business to make data-driven business decisions. Due to these benefits, many companies use it and look towards hiring skilled professionals in it. Here are some of the leading companies that hire professionals with Data Science Online Certification in Qatar.
Deloitte
PwC
Numerator
Amazon and AWS
Splunk
EY
JPMorgan Chase & Co.
Microsoft
Walmart
Databricks
- After completing this course, you will be given a Data Science Online Certification in Qatar. This certification is highly beneficial for you as it acts as proof of your skills and expertise. This Data Science Online Certification in Qatar validates that you are skilled enough to identify business opportunities and forecast future market conditions. It shows a degree of interest and helps you in impressing employers. Having Data Science Online Certification in Qatar enables you to show your potential employer that you are completely serious about your career and job profile. Companies recognize that it is reasonably difficult to secure and earn a Data Science Online Certification in Qatar and thus earning one immediately sets a candidate apart from the crowd. This certification increases your chances of getting the highest-paid job roles in the company.
- Other Related Online Training Courses in Qatar:
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CURRICULUM & PROJECTS
Data Science Training Program
- 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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- 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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- 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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- 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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- 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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- 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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- 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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- 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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WHAT OUR ALUMNI SAYS ABOUT US
Dhruv
1. In recent times Python learning is hugely in demand. And I was looking for an institution to get myself enrolled in this course to become a Data Scientist. They have the best trainers and an affordable fee structure. It's been months now and I am fully satisfied with the trainers, live sessions, Read more...
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Data Science
Enrolling yourself in the Deep learning certification program of Croma Campus is the best way to master all the concepts of data science and deep learning. My experience with these people has been very amazing and positive. The support/guidance I got from the trainer is highly commendable Thanks, te Read more...
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Data Science
Hello, I have joined Croma Campus for a few months in the course helped in acquiring good knowledge. Also, there are many extra classes held by the trainer. There are many mock sessions given after the post completing the course. The salary offered in the industry is high to the candidates. Read more...
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Data Science
I am Pooja Yadav from Haryana. I have joined Croma Campus for learning this course. The trainer helped me to learn advanced practical knowledge and new innovative skills to enhance my ability. Also, the faculty is available in the odd hours for helping. There are many extra reference study materials Read more...
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Data Science
Hi, my name is Sanjeev Kumar. I have recently completed my Django Framework Certification Training from Croma Campus which is the brand name in the domain of technical education. It provides me with well-updated study material which is concerned with the latest industry trends. After the training co Read more...
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Data Science
Croma Campus has well-experienced faculties who are working as a top professional in the industry. I have recently completed my Artificial Intelligence Certification training from this institute and it gives me remarkable experience. With world-class infrastructural facilities, it has a student-frie Read more...
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Data Science
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Abhey
I have joined Croma Campus for taking the Masters in Data Science. It is a good place to learn. Helps in gaining the skills & knowledge. Read more...
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FAQ's
Yes, Data Science is one of the fastest-growing careers and it is certainly not going to slow down. It allows you to program a machine based on multiple parameters to find the best possible business solution to a problem.
That depends on many factors, but there are plenty of certifications out there you could select that require anything from a couple of days to a couple of months of your time.
Yes, it is really worth getting a data science certification if you want to work as a Data Scientist. This certification is the best option on the table for impressing future employers and showcasing your expertise.
Data Scientist's daily work includes defining business problems or opportunities, manipulating data to solve problems, data modeling and testing to provide business solutions, and coding.
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Our learners
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50%
Average Salary Hike
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Placed in MNC’s
15+
Year’s in Training
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fast-tracked into managerial careers.
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