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Data Science Course Objectives

  • Introducing Data Science, Data Analytics and its types.
  • Learning Python, its installations and its basics
  • Python Packages and practice in manipulation of data
  • Application of Data Science in business analysis
  • Big Data analysis through cutting edge tools and technologies
  • Machine learning and Deep learning

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

  • 3: Python Advanced Topics

  • NumPy
  • Create Arrays
  • Array Item Selection and Indexing
  • Array Mathematics
  • Array Operation
  • 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

  • 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

  • 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

  • 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

  • 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

  • 12: NLP

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

  • 13: Deep Learning

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

  • 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


Excellent training. The trainer is an expert in his topics with in-depth knowledge in Data Science and its applications. I thank him a lot in providing a firm base both in theoretical and practical sense.

Data Science Expert

Apponix has the best syllabus that covers all the topics and also meets the future needs. The trainer is so friendly. He has wide knowledge. The classes help in having a real-time experience through numerous practical assignments. Thank you sir.

Data Science Analyst

I joined Apponix for Data Science training. It was a great learning experience. The trainer was too good. Friendly staff and management.

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

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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.

Student Review


Apponix was my best decision. I had the best trainer. The delivery style was so effective. He made sure we understood the concepts clearly. He took the theoretical concepts in simple ways and was easy to understand. Thank you sir and team Apponix.

Amar Koli

I strongly suggest Apponix to my friends. The data Science training at Apponix was too good. The theories were taken in a good style and the practical sessions were so helpful. The classroom experience I got from here helped me a lot in post training career.

Aravind Raj

Hats off to the entire team of Apponix for the great support and effort. Good infrastructure. Facilitated labs and learner-friendly classrooms. Expert trainer who has immense real-world experience. He taught the lessons with immense passion. Thank you sir.

Jasleen Ahuja

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


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.

Salary expectation after completing course

Data Science is one of the growing technical fields with a huge need for professionals required. This has assured 100% placement for one who has completed certification in Data Science. Minimum annual salary of a Data Scientist can be estimated to around 9-10 Lakhs per year. And this will be increased considerably in coming years undoubtedly.

Career after Data Science course

Data Science, being one of the most attracting and demanding career options round the globe, it can be called as “the need of the 21st century. There are billions of dollar investments in this area by MNCs allover the world. 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 ?

  • 28-35% of boost in the field since 2020
  • Expecting massive recruitment
  • Handsome salary ranges from around 3.5 to 10 lakhs per year
  • Majority of the firms are moving to be insights-drive which increases the trends in and around big data, AI, cloud computing, etc. This enhancement of data maturity 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 Training in Chennai

  • Enroll at Apponix for the best technical learning experience in Data Science with Python, one of the most demanding skills in present scenario
  • Apponix provides an unbeatable platform for forming strong theoretical and practical knowledge with immense practical experience
  • Data Science training in Chennai recurrently follows the technological changes and adapt the best possible ideas to the curriculum.


  • What are the job roles waiting?
    • Business Analyst
    • Data Engineer
    • Data Scientist
    • Data Analyst
    • Data Visualizer
  • What will 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
  • 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 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
    • Own study materials
    • Flexible timings and study friendly infrastructure
    • 150+ tied up companies as client to assist in placement