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Data Science Course Objectives

  • Introduction to the fundamentals and advanced concepts of Data Science
  • Understanding Machine Learning, Deep Learning, AI, and Data analytics
  • Learn the application of Data Science in the analysis of business problems
  • Big Data analysis through the employment of cutting edge tools
  • Solving real-world problems using data mining software
  • Learning Python, its installations and its basics
  • Python Packages and practice in manipulation of data

Data Science Course Syllabus

  • 1: Introduction to Data Science

  • Introduction ToDataScience
  • Real Time UseCasesOfDataScience
  • Who is a DataScientist?
  • Github Tutorial
  • Skillsets needed for DataScientist
  • 6 Steps to take in 3 Months for acomplete transformation to DataSciencefrom any other domain
  • Machine Learning-Giving ComputersThe ability to learn from data
  • Supervised vs Unsupervised
  • DeepLearning vs Machine Learning
  • Link to get Free Data to Practice?
  • Some Great self Learning DataScience Resources(Books,Tutorials,Vedeos,Papers)
  • Software Installation

  • 2: Python Programming

  • Introduction To Python
  • “Hello Python Program” in IDLE
  • Jupyter Notebook Tutorial
  • Spyder Tutorial
  • Introduction to Python
  • Variable,Operators,DataTypes
  • If Else,For and While Loops
  • Functions
  • Lambda Expression
  • Filter, Map,Reduce
  • Taking input from keyboard
  • HANDS ON-
  • INTERVIEW QUESTION DISCUSSION

  • 3: Python Advanced Topics

  • NumPy
  • Create Arrays
  • Array Item Selection and Indexing
  • Array Mathematics
  • Array Operation
  • HANDS ON
  • Pandas
  • Introduction to Pandas
  • Series
  • Series indexing and Selection
  • Series Operation
  • Introduction to Pandas
  • Data Frames
  • Data Collection from csv,json,html,excel
  • Data Merging,Concatenation,join
  • Group By and Aggregate Function
  • Order By
  • Missing Value Treatment
  • Outlier Detection and Removal
  • Pandas builtin Data Visualisation
  • HANDS ON
  • INTERVIEW QUESTION DISCUSSION

  • 4: Visualisation-matplotlib, seaborn

  • Line Plots
  • Scatter Plots
  • Pair Plots
  • Histograms
  • Heat Maps
  • Bar Plots
  • Count Plots
  • Factor Plots
  • Box Plots
  • Violin Plots
  • Swarm Plots
  • Strip Plots
  • Pandas BuiltinVisualisation Library
  • HANDS ON
  • INTERVIEW QUESTION DISCUSSION

  • 5: Statistics

  • Descriptive vs Inferential Statistics
  • Mean,Median,Mode,Variance,Std. dev
  • Central Limit Theorm
  • Co-Variance
  • Pearson’s Product Moment Correlation
  • R - Square
  • Adjusted R-Square
  • Spearman’s. Rank order Coefficient
  • Sample vs Population
  • Standardizing Data(Z-score)
  • Hypothesis Testing
  • Normal Distribution
  • Bias Variance Tradeoff
  • Skewness
  • P Value
  • Z-test vs T-test
  • The F distribution
  • The chi-Square test of Independence
  • Type-1 and Type-2 errors
  • Annova
  • HANDS ON
  • INTERVIEW QUESTION DISCUSSION

  • 6: Introduction to Machine Learning

  • Introduction to Machine Leaning
  • Machine Learning Usecases
  • Supervised vs Unsupervised vs Semi-Supervised
  • Machine Learning process Workflow
  • Training a model
  • Validating results
  • Overfitting vs Underfitting
  • Ordinal vs Nominal data
  • Structured vs unstructured vs semi-structured dat
  • Intro to scikitLearn
  • HANDS ON

  • 7: Supervised

  • Regression:
  • Regression Vs Classification
  • Linear regression
  • Multivariate regression
  • Polynomial regression
  • Multi-Colinearity,
  • Auto correlation
  • Heteroscedascity

  • 8: Hands On

  • Classification:
  • KNN
  • Svm
  • Decision Tree
  • Random Forest
  • Performance tuning of Random Forest
  • Naive Bayse
  • Overfitting Vs Underfitting
  • Hands On

  • 9: Validation

  • Classification Report
  • Confusion Report
  • ROC
  • RMSE
  • MSE
  • Cross validation
  • Hands On

  • 10: Unsupervised (Clustering & PCA:)

  • Kmeans
  • How to choose number of K in KMeans
  • Hands on
  • PCA
  • Hands on

  • 11: Ensemble

  • What is Ensembling
  • Types of Ensembling
  • Bagging
  • Boosting
  • Stacking
  • Random Forest
  • Important Feature Extraction
  • XGBoost
  • HANDS ON

  • 12: NLP

  • Tokenizer
  • Stop Word Removal
  • Tf-idf
  • Document similarity
  • Word2vec Model
  • t-SNE visualisation
  • Sentiment Analysis
  • HANDS ON

  • 13: Deep Learning

  • Basic of Neural Network
  • Type of NN
  • Cost Function
  • Tensorflow Basics
  • Hands on Simple NN with Tensorflow
  • Image classification using CNN
  • HANDS ON

  • Project 1: Sale Prediction

  • In this project, we will build a predictive model to find out the sales of each product at a particular store.

  • Project 2: Predict Taxi Destination

  • In this project, we will build a predictive framework that is able to infer the final destination of taxi rides based on their (initial) partial trajectories. The output of such a framework will be the final trip's destination employee's attributes change over time.
Download Full Data Science Trainig Course Syllabus Now

Students Feedback for Data Science Training

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Sanjay

Thank you Apponix for giving me such a better training in Data Science. The trainer is an expert. He shares the best knowledge through sufficient examples.

Data Science Expert
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Shailesh

Well organized classes without the usual boring of online classes. The trainer has in-depth knowledge in the subject. I thank Apponix for helping me to overcome the fear of studying the complex concepts in Data Science.

Data Science Analyst
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Priyanka

Best online training. The classes are very clear and understandable. The instructor was exceptionally knowledgeable and calm. He teaches every concept in its deepest sense.

Data Science Analyst
subrat Mr.Sreedhar

Data Science & Python Trainer 10+ Years Of Working Experience In MNC.

Data Science Trainer Profile

  • 8+ years of Experience in Data Science, currently spearheading the efforts.
  • Trained more than 2000+ students on Data Science at Apponix.
  • 5-star rating from all Data Science students.
  • Well versed in Data Science.
  • Excellent training delivery skills with an ability to present information well.
  • Demonstrable experience of being student focused and completing projects to hit deadlines and targets.
  • Demonstrable proof of enthusiasm, initiative, creativity and problem solving.
  • Demonstrable experience in delivering quality training on Data Science.
  • Excellent practical experience.

Apponix Ratings

apponix +11000 Satisfied Learners

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Enroll for Data Science training today

Join Apponix for the best competitive training in Data Science under profiecient trainer who are real industry experts.

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Student Review

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Sagar

I enrolled at Apponix for Data Science online training. It was a great experience. The training provided with good real time examples which helped a lot in understanding the concepts well. Thank you sir and the entire team of Apponix

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Amar Koli

Great learning experience. They offer facilities for doubt clearance and the trainer does that without any delay. The syllabus covered vast area in data science concepts and its applications.

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Aravind Raj

Data science training from Apponix helped a lot in pursuing a better career. Unlike other online training, it provides a feeling of classroom experience. The assignments they give and the questions discussed were really helpful in post training tests and interviews. Thank you Apponix.

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Jasleen Ahuja

i completed SEO course here .Akash sir is an excellent trainer! I had a great experience learning here!

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Shoba

Apponix the one of the best institute for Digital Marketing and SEO. The way of teaching by Akash sir is fantastic, here i learned many things.

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Salary expectation after completing course

Data Science professionals are now in the list of one of the most demanding careers with constantly rising salary. Presently, the average annual salary of a Data Scientist is around INR 9-10 lakhs.

Career after Data Science course

One of the most attracting and demanding careers with millions of job opportunities around the globe. Billions of dollars are invested in this area by various reputed MNCs. 70% of market growth is predicated by the experts in this field which is the best proof to assure 100% placement in various job roles after the training.

Why Should You Learn Data Science?

  • Since 2020, experts have estimated a growth of around 30% in this field
  • Massive recruitment around the globe
  • Salary ranges from around 3.5 to 10 lakhs per year
  • Massive shift of firms to insights-drive which increases the trends in and around big data, AI, cloud computing etc. This enhancement heightened the need of data science.
  • Huge investment of MNCs in Big Data and AI sectors which demands greater implementations of Data Science
  • Along with analyzing and comprehending the data trends, a data scientist has to interpret and decipher the laws in an appropriate and approachable manner for the business tycoons, and also formulate advance solutions over it.

Data Science Online Training

  • Apponix offers best experience in the history of online trainings
  • We deviate from the traditional structure.
  • Our trainers are well-informed and well-experienced both in professional and training platforms. We provide the facility of quick doubt clarification.

FAQs

  • Why should I choose Apponix?
    • Most experienced professional as trainers.
    • Continuous tracking of the needs of different industries and prepares the trainees for the upcoming trends in markets and technologies.
    • Enables the aspirants be prepared for the future interviews and tests.
    • 5 star rating and 98% student satisfaction
    • Customised syllabus
    • Resume preparation
  • What skills can I learn through this training?
    • Testing analysing and managing data of organizations
    • Predicting breakdowns using various tools
    • Offering best solutions and best possible innovations
    • Sampling techniques
    • Installation and working with analytical tools
    • Deploying cluster for analysis
  • What are the job roles waiting?
    • Business Analyst
    • Data Engineer
    • Data Scientist
    • Data Analyst
    • Data Visualizer
  • Which are the fields offering career opportunities for Data Scientists?
    • AI
    • E-commerce
    • Travel & Tourism
    • Banking
    • Telecommunications
    • Health
    • Education
    • Finance
  • Which all reputed firms will hire Data analytics professionals?
    • IBM
    • Dell
    • Microsoft
    • Infosys
    • Wipro
    • Amazon
    • Flipkart
    • Snapdeal
    • TCS and so on,
  • Why to Choose Apponix?
    • Excellent and qualified trainers
    • Dedicated HR team & 1000+ placements
    • 7000+ happy students.
    • Excellent lab facility & AC classrooms.
    • 100% student satisfaction rate.

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