Data Analytics with Python
Training in Data Analytics with Python significantly boosts your career prospects, offering opportunities in high-demand roles such as Data Analyst, Data Scientist, Machine Learning Engineer, and Business Intelligence Analyst. The versatile skillset you gain allows for efficient data cleaning, exploration, and visualization, leveraging robust libraries like Pandas and NumPy.
Python's community support and scalable capabilities make it a powerful tool for handling large datasets and complex analyses. By mastering Python for data analytics, you enhance your problem-solving skills and strategic decisionmaking abilities, making you a valuable asset to any data-driven organization.
Benefits of Python Training
- Versatility: Python is used across multiple domains, including data analysis, machine learning, and web development.
- High Demand: Python expertise is a top requirement for roles like data scientist, software developer, and machine learning engineer.
- Open-Source Ecosystem: Access to a vast library of tools and frameworks to solve diverse problems.
- Scalable Career Path: Entry-level skills can evolve into advanced areas like AI, data engineering, and automation.
- Competitive Salaries: Python-trained professionals earn competitive salaries in tech-driven industries.
Course Detail
| TOPIC | SUB TOPIC | DAY |
TOTAL DAYS |
| IDLE SETUP AND PYTHON INTRO | IDLE INSTALLATION , BASIC INTRO OF PYTHON | DAY1 | 3 |
| VARIABLE/IDENTIFIERS,DATA TYPES,IP/OP | DAY2 | ||
| INPUT,RAW_INPUT,FLUSH=FALSE,END="\N" | DAY3 | ||
| OPERATORS IN PYTHON | OPERATORS IN PYTHON(ARITHMATIC & LOGICAL) | DAY4 | 2 |
| OPERATORS IN PYTHON(REMAINING & PRECEDENCE & MCQ) | DAY5 | ||
| CONDITIONAL STATEMENTS | CONDITIONAL STATEMENTS(IF,NESTED IF,LOGICAL OP) | DAY6 | 3 |
| BASIC LEVEL QUESTIONS (CONDITIONAL STATEMENT) | DAY7 | ||
| ADVANCE LEVEL QUESTIONS (CONDITIONAL STATEMENT) | DAY8 | ||
| STRINGS IN PYTHON |
STRINGS IN
PYTHON(INTRO,ACCESSING ELEMENTS,PYTHON CONSTRUCTORS) |
DAY9 | 4 |
| ATTRIBUTES (PYTHON STRING) | DAY10 | ||
| STRING FORMATTING AND PRINTING AND ESCAPE CHARACTERS IN STR | DAY11 | ||
|
ADVANCE
INTERVIEW QUESTION ON PYTHON STRING(SLICING+ATTRIBUTES) |
DAY12 | ||
| ITERATIVE STATEMENTS (WHILE LOOP) | ITERATIVE STATEMENTS(WHILE LOOP INTRO,SET1-SET2-SET3 TASK) | DAY13 | 4 |
| STATEMENTS USED WITH LOOPS(BREAK,CONTINUE,PASS)+ADVANCE QUESTIONS-HW | DAY14 | ||
| QUESTION SET(31 QUES)-SOLVING | DAY15 | ||
| QUESTION SET(31 QUES)-SOLVING | DAY16 | ||
|
RANDOM
MODULE+IF STATEMENT |
RANDOM MODULE INTRO+ (DICE ROLL) +(STONE PAPER SCISSOR GAME SINGLE ROUND [ROUND=1 ]) | DAY17 | 1 |
| RANDOM MODULE+ IF STATEMENT+ WHILE LOOP | (STONE PAPER SCISSOR GAME MULTIPLE ROUND[ROUNDS>1] ) + ANY SMALL GAME DEVELOPMENT BY STUDENTS USING RANDOM MODULE | DAY18 | 1 |
| OPERATIONS OF STRING | TRAVERSAL | DAY19 | 3 |
| SEARCHING & SORTING | DAY20 | ||
| STRING _ LOOP ADVANCE QUESTION | DAY21 | ||
| LIST IN PYTHON | LIST (INTRO,ACCESSING ELEMENTS,PYTHON CONSTRUCTORS,ATTRIBUTES) | DAY22 | 6 |
|
MULTIDIMENSIONAL
LIST(INTRO,ACCESSING ELEMENTS,PYTHON CONSTRUCTORS) |
DAY23 | ||
| TRAVERSAL,SEARCHING,SORTING OF LIST (USING WHILE LOOP) | DAY24 | ||
| LIST COMPREHENSION IN PYTHON | DAY25 | ||
| MATRIX INTRO AND OPERATIONS | DAY26 | ||
| INTERVIEW QUESTIONS LITS +LIST AUTOMATION | DAY27 | ||
| TUPLE IN PYTHON | TUPLE (INTRO,ATTRIBUTES,STRING COMPARE TASK) | DAY28 | 7 |
| TUPLE AUTOMATION + INTERVIEW QUESTION | DAY29 | ||
| ITERATIVE STATEMENTS (FOR LOOP) | ITERATIVE STATEMENTS(WHILE LOOP INTRO,SET1-SET2-SET3 TASK) | DAY30 | |
|
STATEMENTS USED WITH LOOPS(BREAK,CONTINUE,PASS)+ADVANCE QUESTIONS-HW |
DAY31 | ||
| QUESTION SET(31 QUES)-SOLVING USING FOR LOOP | DAY32 | ||
| TRAVERSAL OF ALL ARRAYS USING FOR LOOP | DAY33 | ||
|
MATRIX(ADDITTION,ROW
COLUMN TRANSPOSE,MULTIPLICATION,CREATION) |
DAY34 | ||
| DICTIONARY IN PYTHON | DICTIONARY INTRO(ACCESSING,TRAVERSAL,METHODS) | DAY35 | 2 |
| ADVANCE QUESTIONS ON DICRTIONARY | DAY36 | ||
| SETS IN PYTHON | INTRODUCTION TO SETS(METHODS,QUESTIONS) | DAY37 | 3 |
| OPERATION OF SETS & COMPARSION WITH DICTIONARY | DAY38 | ||
| ADVANCE QUESTIONS FOR TRAVERSAL | DAY39 | ||
| DATE TIME MODULE IN PYTHON | DATE AND TIME MODULE INTRO(ALL ATTRIBUTES EXPLORE) | DAY40 | 3 |
|
CURRENT TIME
,FORMATTING,DERIVING DATES & CREATING DATE OBJECTS |
DAY41 | ||
| TIME MODULE | DAY42 | ||
| FUNCTIONS IN PYTHON | FUNCTION INTRO,2 CATEGORY,3 TYPES,CREATION & INVOKE,ARGUMENT & PARAMETER(3 TYPES) | DAY43 | 6 |
| SCOPE OF VARIABLE,GLOBAL/NON LOCAL KEYWORD,FLOW OF EXECUTION,ARG AND KEY ARG | DAY44 | ||
| RECCURSION INTRO | DAY45 | ||
| RECCURSION INTRO + ADVANCE QUESTIONS | DAY46 | ||
| PYTHON REGULAR EXPRESSION | DAY47 | ||
| PYTHON LAMBDA FUNCTION | DAY48 | ||
| PYTHON MODULES IMPORT | CREATION,RENAME,VARIABLE DECLARATION | DAY49 | 2 |
| BUILT IN MODULE INTRO,LIBRARY EXAMPLES,IMPORTING MODULES | DAY50 | ||
|
PIP IN PYTHON
(ADDING /REMOVING PACKAGES) |
PIP
INTRO,INSTALLATION,DOWLOADING A PACKAGE,USING A PACKAGE,FIND & REMOVE |
DAY51 | 2 |
| LIST OF PACKAGES AND VERSION | DAY52 | ||
| EXCEPTIONAL HANDLING IN PYTHON | TYPES OF EXCEPTION IN PYTHON | DAY53 | 4 |
| TRY,EXCEPT,ELSE,FINALLY | DAY54 | ||
| RAISE AN EXCEPTION + ADVANCE QUESTIONS | DAY55 | ||
| OOPS IN PYTHON | CLASS AND OBJECT INTRO& EXAMPLE & SYNTAX, INIT ,PARAMETER PASSING,INPUT | DAY56 | 9 |
|
INIT (), STR (),OBJECT METHOD ,SELF PARAMETER,MODIFY,DELETE |
DAY57 | ||
| TYPES OF INHERITANCE(CODE AND EXAMPLE ) | DAY58 | ||
| REMAINING TYPES+ITERATORS+ CREATION OF ITERATORS + STOPPING ITERATION | DAY59 | ||
|
POLYMORPHISM(FUNCTION,OPERATOR,CLASS
POLY,INHERITANCE CLASS POLY) |
DAY60 | ||
| OPERATOR OVERLOADING AND FUNCTION OVERLAODING | DAY61 | ||
| ENCAPSULATION AND ACCESS MODIFIERS | DAY62 | ||
| ABSTRACT BASE CLASS,ABSTRACTION | DAY63 | ||
| QUESTION SET INTERVIEW PRACTISE | DAY64 | ||
| DSA IN PYTHON | LIST,TUPLE,SET,FROZEN SET,DICTIONARY,STRING,MATRIX | DAY65 | 25 |
| FROZEN SET,MATRIX,BYTEARRAY | DAY66 | ||
| STATCK,QUEUE | DAY67 | ||
| INTERVIEW QUESTION STACK | DAY68 | ||
| INTERVIEW QUESTION QUEUE +PRIORITY QUEUE | DAY69 | ||
| LINKED LIST INTRO | DAY70 | ||
| LINKED LIST QUESTIONS INTERVIEW | DAY71 | ||
| HEAP | DAY72 | ||
| QUESTIONS HEAP | DAY73 | ||
| BINARY TREEE | DAY74 | ||
| QUESTIONS BINARY TREE | DAY75 | ||
| TREE TRAVERSAL,BREADTH FIRST(0-LEVEL) | DAY76 | ||
| BINARY SEARCH TREE | DAY77 | ||
| QUESTIONS | DAY78 | ||
| GRAPH | DAY79 | ||
| GRAPH QUESTIONS | DAY80 | ||
| ADJACENCY MATRIX,ADJACENCY LIST | DAY81 | ||
| GRAPH TRAVERSAL(BFS,DFS) | DAY82 | ||
| RECCURSION | DAY83 | ||
| DYNAMIC PROGRAMMING(TABULATION & MEMORIZATION) | DAY84 | ||
| SEARCHING ALGORITHMS(LINEAR,BINARY) | DAY85 | ||
| SORTING ALGORITHMS(SELECTION,BUBBLE,INSERTION) | DAY86 | ||
| SORTING ALGORITHMS(MERGE,QUICK) | DAY87 | ||
| PARTION ALGORITHM | DAY88 | ||
| SHELLSORT | DAY89 | ||
| FILE HANDLING IN PYTHON |
FILE
HANDLING INTRO(TYPES OF FILES)(BINARY VS
TEXT)(OPENING AND CLOSSING)(DIRECTORY) |
DAY90 | 7 |
| MODES IN FILE HANDLING(TEXT),OPEN,CLOSE,APPEND,READ,WRITE | DAY91 | ||
| ADVANCE QUESTIONS FOR TEXT FILE(21) | DAY92 | ||
| PICKLE MODULE & SERIALIZATION AND DESERIALIZATION OF DATA | DAY93 | ||
| BINARY FILE(OPEN,CLOSE,APPEND,READ,WRITE) | DAY94 | ||
| CSV MODULE(OPEN,CLOSE,APPEND,READ,WRITE) | DAY95 | ||
| QUESTIONS OF CSV EXCEL FILE | DAY96 | ||
| MYSQL CONNECTION | SETUP SERVER CONNECTION,INSTALLATION,CONNECTION OBJECT | DAY97 | 7 |
| CURSOR OBJECT,FETCH COMMANDS | DAY98 | ||
| MySQL CREATE,TABLE,INSERT,WHERE,ORDER BY,DELETE,DROP | DAY99 | ||
| MYSQL UPDATE,LIMIT,JOIN | DAY100 | ||
| PROJECT1 | DAY101 | ||
| PROJECT1 | DAY102 | ||
| PROJECT2-BY STUDENTS | DAY103 | ||
| GUI IN PYTHON | Introduction,What is Tkinter for Python?GUI,LABEL,ENTRYBOX,WIDGET,IMAGE,FRAME | DAY104 | 6 |
| WIDGET(19),PACKER(3) | DAY105 | ||
| MENU,SUBMENU,SRC | DAY106 | ||
| PROJECT1 | DAY107 | ||
| PROJECT1 | DAY108 | ||
| PROJECT2 | DAY109 | ||
| ADVANCE PYTHON FOR DATA ANALYST | |||
| NUMPY | NUMPY INTRODUNCTION | DAY110 | 18 |
| ARRAY CREATION ROUTINE | DAY111 | ||
| INTRO ,CREATING ARRAY INDEXING,NUMPY ARRAY SLICING,NUMPY DATA TYPES | DAY112 | ||
|
NUMPY COPY VS
VIEW,NUMPY ARRAY SHAPE,NUMPY ARRAY RESHAPE,NUMPY ARRAY |
DAY113 | ||
| ITERATINGNUMPY ARRAY, JOINNUMPY ARRAY, SPLITNUMPY ARRAY | DAY114 | ||
| SEARCHNUMPY ARRAY SORTNUMPY ARRAY FILTER | DAY115 | ||
| NUMPY RANDOM | DAY116 | ||
| RANDOM INTRODATA DISTRIBUTION ,RANDOM PERMUTATION | DAY117 | ||
| SEABORN MODULE | DAY118 | ||
| SEABORN MODULE QUESTIONS | DAY119 | ||
|
NORMAL DISTRIBUTION
,BINOMIAL DISTRIBUTION,POISSON DISTRIBUTION |
DAY120 | ||
| UNIFORM DISTRIBUTION,LOGISTIC DISTRIBUTION,MULTINOMIAL DISTRIBUTION,EXPONENTIAL DISTRIBUTION | DAY121 | ||
| CHI SQUARE DISTRIBUTION,RAYLEIGH DISTRIBUTION | DAY122 | ||
| PARETO DISTRIBUTION,ZIPF DISTRIBUTION | DAY123 | ||
| NUMPY UFUNC INTRO | DAY124 | ||
| UFUNC CREATE FUNCTIONUFUNC SIMPLE ARITHMETIC | DAY125 | ||
| UFUNC ROUNDING DECIMALS SUMMATIONS PRODUCTS DIFFERENCES,FINDING LCM & GCD | DAY126 | ||
|
UFUNC TRIGONOMETRIC &
UFUNC HYPERBOLIC & UFUNC SET OPERATIONS |
DAY127 | ||
| PANDAS | PANDAS INSTALL BASIC INTRO | DAY128 | 8 |
| PANDAS SERIES ,DATAFRAMESPANDAS | DAY129 | ||
| PANDAS READ CSVPANDAS READ JSON | DAY130 | ||
| ANALYZING DATA | DAY131 | ||
| CLEANING DATA( EMPTY CELLS,WRONG FORMAT,DUPLICATE HANDLING) | DAY132 | ||
| PANDAS CORRELATION-I | DAY133 | ||
| PANDAS CORRELATION-II | DAY134 | ||
| PANDAS PLOTTING | DAY135 | ||
| MATPLOTLIB | THE DATASET HANDLING | DAY136 | 13 |
| LOADING MATPLOTLIB | DAY137 | ||
| DRAWING LINE PLOTS | DAY138 | ||
| LINE PLOTS WITH A SINGLE LINE | DAY139 | ||
| LINE PLOTS WITH MULTIPLE LINEZ | DAY140 | ||
| ADDING A LEGEND | DAY141 | ||
| DRAWING BAR PLOTS | DAY142 | ||
| VERTICAL BAR PLOTS | DAY143 | ||
| REORDERING BARS IN BAR PLOTS | DAY144 | ||
| HORIZONTAL BAR PLOTS | DAY145 | ||
| DRAWING SCATTER PLOTS | DAY146 | ||
| SETTING THE PLOT TITLE AND AXIS LABELS | DAY147 | ||
| CHANGING COLORS | DAY148 | ||
| MACHINE LEARNING IN PYTHON | MEAN MEDIAN MODE | DAY149 | 17 |
| STANDARD DEVIATION,PERCENTILE | DAY150 | ||
| DATA DISTRIBUTION,NORMAL DATA DISTRIBUTION | DAY151 | ||
| SCATTER PLOT | DAY152 | ||
| REGRESSION(LINEAR AND POLYNOMIAL & MULTIPLE) | DAY153 | ||
| SCAELL, TRAIN/TEST | DAY154 | ||
| DECISION TREE | DAY155 | ||
| CROSS VALIDATIONAUC - ROC CURVEK-NEAREST NEIGHBORS | DAY156 | ||
| HIERARCHAL CLUSTERING | DAY157 | ||
| LOGISTIC REGRESSION | DAY158 | ||
| GRID SEARCH | DAY159 | ||
| CATEGORICAL DATA | DAY160 | ||
| K MEAN | DAY161 | ||
| BOOTSTRAP AGGREGATION | DAY162 | ||
| CROSS VALIDATION | DAY163 | ||
| AUC - ROC CURVE | DAY164 | ||
| K-NEAREST NEIGHBORS | DAY165 | ||
| LIVE PROJECT WITH INTELLUS DIRECT | |||
| LIVE PROJECT WITH INTELLUS PRIME | |||