Onlinetutorials.today provides online data science training course from experienced faculty.

Here is the course syllabus:

**Introduction data science:**

- What is data science
- What is AI
- What is machine learning
- What is deep learning

**Statistics:**

- Probability
- Types of statistics
- Descriptive statistics
- Measures of central tendency
- Measures of spread
- Central limit theorem
- Distribution
- 7 Different types of distributions:
- Normal Distribution
- Binomial distribution
- poisson distribution
- Probability density functions
- Characteristics of normal distribution
- Sampling
- Sampling methods
- Inferential statistics
- P value and Z value
- Hypothesis testing (t-test, f-test, chi-square)
- Analysis of variance
- Measures of relationship:
- Correlation
- Regression
- Co-variance
- Associations
- Odds Ratio

**Introduction to R-Programming**

- R and R-studion installation
- Data types and data structures
- Arithmetic and logical operations
- Conditional statements
- Loops
- Packages and functions in R
- Data Frame operations
- Getting data into R from flat files
- Connecting to databases
- Data Inspection and Manipulation
- Data wrangling an data munging

**EDA(Exploratory data analysis and visualization)**

- Summary statistics
- Data distributions
- Data transformations
- Outlier detection and management
- One dimensional chats
- Charts an Graphs
- Histogram
- Barchart
- Two dimensional
- Scatter plots
- Bar charts
- Box plots
- Multi-dimensional plots
- Bubble charts and word clouds
- Inference and Variable selection

**Data Pre-processing:**

- Data types an conversions
- Binning and Normalization
- Min-max scaling
- Imputation
- Dimensionality reduction

**Machine Leaning Online Training:**

**Introduction**

- Types learning
- Supervised learning
- Unsupervised learning
- Reinforcement learning

**Supervised learning Algorithms:**

**Regression:**

- Linear Regression
- Simple liner Regression
- Variable Selection
- Model Development
- Gradient descent approach
- Regression Metrics
- Ridge regression
- Lasso regression
- Elastic Net Regression

**Classification:**

- Logistic Regression
- SVM
- Decision Trees
- Random Forest
- Naive Bayes
- KNN
- Classification Metrics
- Confusion matrix
- Precision
- Recall
- F1-score

- cross validation
- parameter tuning

**Bagging:**

- Ensemble methods
- Random Forest

**Boosting:**

- Adaboost
- Gradient boosting
- Xgboost

**Unsupervised Algorithms**

- Clustering Algorithms
- K-means
- Hierarchical Clustering
- Dimenationality Reduction
- SVD
- LDA
- PCA -Principal component analysis

**Reinforcement learning**

- Q-learning

**Working Text Data**

- Pre processing
- Tokenization
- Stemming
- Lemmatising
- POS Tagging
- Count vectizer
- Bag of words
- TF-IDF approach
- Sentiment analysis

**Time series analysis**

- Introduction
- Stationary and non stationary data
- Trend, Seasonality, Randomness
- Moving Average Method
- Exponential smoothing
- ARIMA

**Machine learning with Python**

- Introduction to Python
- Variables
- Operators
- Loops
- Functions
- Lists
- Tuples
- Dictionaries
- List comprehensive
- Numpy:
- Scipy:
- Pandas:
- Matplotlib:
- Scikit-learn:

**Introduction to Deep learning:**

- Neural Network
- Types of networks
- Feed forward network and Back forward network
- CNN
- RNN
- LSTM
- Gradient boosting

**Recommendation systems:**

- Matrix factorization
- collaborative filtering
- user based collaborative filtering
- item based collaborative filtering

**Association rules**

- Market Basket Analysis
- Apriori

**FAQ’s**

**Why data science ?**

Data science is the sexiest job for the 21st century. More job openings with less crowded. Start leaning

**Who is Data scientist ? **

More than program and more than a statistician

**What is average salary for data scientist ?**

$102,000 in USA

**How to become a data scientist ?**

you need to learn statistics and programming

Is there any free resources to practice data science online ?

**Is there any data science learning sources ? **

Analyticsvidhya, Towards datascience, kaggle, youtube videos are good to learn data science. If you are registered for this course, you will learn data science in 3 months.

How to use kaggle for data science ?

**I am a fresher, Can i learn data science ?**

Yes

**I am experienced developer. Can i change my carrier to data science ? **

Yes.

**What is the course Fee ?**

Rs.49999 or $705

**Is it online course ? **

Yes

**Do you have any classroom training ? **

No

**What is Refund policy ? **

We don’t have any refund policy, First we will provide the demo class, If you are interested you can enroll for online classes.

**What is duration of course ?**

90 Days

**What is Class Timings ?**

Daily 60 mints